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International Journal of Embedded Systems

 

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International Journal of Embedded Systems (105 papers in press)

 

Regular Issues

 

  • On the security of a security-mediator-based sharing stored data in the cloud   Order a copy of this article
    by Jianhong Zhang, Qiaocui Dong, Jian Mao, Xu Min 
    Abstract: As an important service of cloud computing, the cloud storage can relieve the burden for storage management and maintenance since the data owners' data are moved to the cloud from their local computing system. However, after data are outsourced to the cloud, data owners no longer physically possess the storage of their data. To ensure the correct storage of the outsourced data, data owners need to periodically execute the integrity verification of data. However, in most existing data integrity checking protocols, a data owner's identity is inevitably revealed to public verifiers in the process of integrity verification. Recently, in order not to compromise the privacy of data owners' identity and not to increase overheads significantly, Wang et al proposed an efficient publicly verifiable approach to ensure cloud data integrity by including a security mediator. The identity of the data owner is hidden through the signature, which is produced by the security mediator. Unfortunately, in this paper, we show that their scheme is insecure. It is prone to unforgeability attack, tamper attack and active attack.
    Keywords: attack; tamper attack; active attack; data integrity checking; security analysis; cloud storage.

  • A local HMM for indoor positioning based on fingerprinting and displacement ranging   Order a copy of this article
    by Ayong Ye, Jianfei Shao, Zhijiang Yang 
    Abstract: Hidden Markov models (HMMs) are powerful probabilistic tools for modelling sequential data, and have been applied to indoor positioning tentatively by combining RSSI fingerprinting method with inertial sensors. In that case, positioning is considered as from an isolated location estimating to a sequential locations transition process. Then the positioning is transformed to the prediction problem in HMMs. However, because the location estimating depends on the previous estimated location and its estimating error, the cumulative error and the resonance error may increase in a continuous positioning process over time. This paper presents an approach to divide the whole continuous positioning process into specified-size sub-processes, and each of them is independent. For this approach, the cumulative and resonance error caused by iterative estimation could be reduced efficiently. Meanwhile, we develop a prototype system, and conduct comprehensive experiments. The evaluation results demonstrate the effectiveness of the proposed approach.
    Keywords: indoor positioning; hidden Markov models; RSSI fingerprinting; displacement ranging; Wi-Fi; accelerometer.

  • An increased resilience fault-tolerant framework for a navigation, guidance, and control system with augmented resources   Order a copy of this article
    by Archana Sreekumar, Radhamani Pillay V 
    Abstract: Onboard computers use redundant hardware for fault tolerance resulting in underutilisation of resources under fault-free condition. This paper exploits the resource augmented model, in which task allocation based on task criticality ensures safe minimal functionality under permanent fault. An algorithm has been designed for real time scheduling with fault tolerance and precedence constraints for a hot standby dual redundant navigation (N), guidance (G), and control (C) system. This algorithm is designed for recovery under permanent hardware fault in different case studies of single, double and triple units of different types (N,G,C). It can tolerate permanent software failures, transient hardware and software failures occurring as a single or combinations in the same type unit. Tolerating increased frequency of transient and software faults with the same allowable safety margins and an increased flexibility in enhanced operational performance by different operational modes under fault and fault free condition without degrading safety margins are significant performance aspects of this design.
    Keywords: safety critical systems; onboard computer; resource augmentation; fault tolerance; dual redundant; permanent fault; transient fault; software fault; forward and backward recovery; uniform checkpointing; space and time redundancy; task criticality.

  • A holistic approach to energy-aware design of cyber-physical systems   Order a copy of this article
    by Jose Antonio Esparza Isasa, Peter Gorm Larsen, Fin Overgaard Hansen 
    Abstract: In this paper, we present a new approach to the design of Cyber Physical Systems (CPSs) with limited energy availability. CPSs are normally composed of subsystems of very different nature, such as electromechanical, computational or communication subsystems. Despite this heterogeneity all of them consume energy, making this a cross-cutting concern. This approach is said to be holistic because it addresses all the subsystems that compose the CPS in a joint design effort, hence tackling the energy consumption challenge effectively. Additionally, modelling is used to support it using different methods and tools depending on the subsystem under consideration. This approach has been applied to two different case studies: the development of a compression stocking to treat leg-venous insufficiency and the development of a wearable heart monitor. In both cases its application has enabled the understanding of the system's energy consumption better and from different angles, providing useful input to the creation of energy-efficient realisations.
    Keywords: energy-aware design; cyber-physical systems; model-driven engineering.

  • EEG processing: a many-core approach using the Intel Single-Chip Cloud computer platform   Order a copy of this article
    by Gildo Torres, Paul McCall, Chen Liu, Mercedes Cabrerizo, Malek Adjouadi 
    Abstract: Epilepsy is the most frequent neurological disorder other than stroke. The electroencephalogram (EEG) is the main tool used in monitoring and recordings brain signals. In this study, we target two detection algorithms that are essential in the diagnosis of epileptic patients. These algorithms detect high frequency oscillations (HFO) and interictal spikes (IIS) in subdural EEG recordings respectively. This paper presents the efforts on porting both EEG processing algorithms into Intel's concept vehicle, the Single-Chip Cloud Computer (SCC), a fully programmable 48-core prototype provided with an on-chip network along with advanced power management technologies and support for message-passing. Several experiments are presented for different SCC configurations, where we vary the number of cores used and their respective voltage/frequency settings. The application was decomposed into two execution regions (i.e. load and execution). Results are presented in the form of performance, power, energy, and energy-delay product (EDP) metrics for each experiment.
    Keywords: Intel SCC; many-core; EEG processing; high frequency oscillation; interictal spike; power-aware computing

  • Efficient iceberg join processing in wireless sensor networks   Order a copy of this article
    by Yongxuan Lai, Xing Gao, Tian Wang, Ziyu Lin 
    Abstract: A new class of monitoring applications is emerging, in which multiple embedded devices are deployed to sense the physical world and a large amount of data is injected into the network. Yet existing monitoring algorithms usually output a result set that is trivial for users and too expensive for the resource-constraint network. In this paper, we study the problem of iceberg join processing in wireless sensor networks. The iceberg join query only includes a small fraction of data in its result set, yet still contains the most interesting and useful data relationships and linkages of the sensing data. The proposed algorithm SRJA is output sensitive and adopts a progressive refinement strategy for the query processing. Our algorithm first constructs flexible synopses according to the characteristics of the joining data, and then progressively refines these synopses to identify tuples that can match and meet the iceberg threshold in the joining regions. It fully uses the iceberg threshold to filter out tuples that do not contribute to the final result set at early stages, saving lots of transmissions. Extensive experiments indicate that our algorithm gains a reduction up to 25% of message transmissions compared with other schemes.
    Keywords: synopsis refinement; iceberg join queries; sensor network.

  • Revocable hierarchical identity-based encryption over lattice for pay-TV systems   Order a copy of this article
    by Leyou Zhang, Zongchen Sun, Yi Mu, Yupu Hu 
    Abstract: If the subscribers certificate has expired or been revealed, a revocable mechanism is needed in a dynamic pay-TV system. Considering the hierarchical structure in this system, a revocable hierarchical identity-based encryption (RHIBE) scheme is a better choice than other schemes. But the well-known RHIBE schemes are constructed on the bilinear pairings which are denoted by the high computation cost and are not efficient in real life. In this paper, two efficient and practical schemes are issued on lattice. Our first scheme is secure against adaptive identity-time attacks in the Random Oracle (RO) model, and the second is secure against selective identity-time attacks in the standard model. The security of both schemes is reduced to the learning with errors (LWE) assumption. In particular, the proposed schemes' basis delegation algorithms are run in the fixed dimension, and the ciphertexts are shorter than existing schemes. Both schemes are much more efficient than the known works in terms of computation cost and storage cost.
    Keywords: pay-TV; revocable HIBE; lattice; learning with errors; subset-cover revocation.

  • Expressive ciphertext-policy attribute-based encryption with direct user revocation   Order a copy of this article
    by CuiCui Bai, Yinghui Zhang, Hua Ma, Zhenhua Liu 
    Abstract: Attribute-based encryption enables fine-grained access control on sensitive data with a specific user set, which is determined by attributes. However, traditional ABE schemes cannot satisfy practical requirements of data-sharing applications, in that users may leave or join a system frequently. In this paper, a ciphertext-policy ABE scheme with direct user revocation (DUR-CP-ABE) is proposed. In DUR-CP-ABE, both the private key and the ciphertext contain partial components associated with a user identity and a revocation list, respectively. A user can decrypt a ciphertext if and only if he/she is not in the revocation list and his/her attribute set satisfies the access policy, simultaneously. In addition, whenever revocation events occur, only ciphertext components associated with the revocation list need to be updated, and non-revoked users do nothing. Finally, the DUR-CP-ABE scheme is proved selectively secure under the Decisional q-Bilinear Diffie-Hellman Exponent assumption in the standard model, where q is determined by the number of users. Compared with existing revocation-related schemes, the new scheme can achieve high efficiency and ensure the expression ability of access structure.
    Keywords: attribute-based encryption; user revocation; access control; data sharing

  • Context-driven composition for mobile applications: a metamodelling approach   Order a copy of this article
    by Afrah Djeddar, Hakim Bendjenna, Abdelkrim Amirat 
    Abstract: The numbers and types of applications (apps) that are, and are becoming, available on a variety of platforms for mobile devices is undeniably explosive. This phenomenon is likely to encourage the user of a mobile device to expect more or less the same app to be available on just about any kind of platform, even when there are differences in the platforms as well as in the apps that run on such platforms. In order to better fulfil the users expectations, understanding such differences or heterogeneities then becomes critical, as does resolving them, but is quite challenging. In this paper, we propose a technique for developing mobile device apps, through composition of existing homogeneous or heterogeneous apps (or software entities), that are context-aware i.e., customise behaviour of the desired app according to the different execution environments and users needs. As a key novelty, this technique uses a metamodelling approach to understanding and representing the differences, as well as commonalities, between different apps. In this approach, description languages are used to define the desired mobile app at several different levels of abstraction, where the passage among them is established using transformation mechanisms. As another key novelty, this technique resolves the differences that can be produced by dint of users needs and contextual information of the execution environment by detecting the different heterogeneity points and associating appropriate mediators when a heterogeneous coordination is needed. In order to see the applicability and the effectiveness of this technique, a tool has been implemented to date, together with an application to a shop review app.
    Keywords: composition; mobile apps; reusing software entities; heterogeneity; context-aware; metamodelling.

  • Energy-efficient real time scheduling algorithm for mixed task set on multi-core processors   Order a copy of this article
    by Mayuri Digalwar, Praveen Gahukar, Biju Raveendran, Sudeept Mohan 
    Abstract: Energy optimisation is gaining greater significance in a wide range of systems from mobile devices to data centres. Specifically, in battery-powered real time embedded systems where tasks are executed under hard timing constraints, energy optimisation poses a big challenge. This paper focuses on dynamic energy optimisation using a well established technique namely Dynamic Voltage and Frequency Scaling (DVFS). This work presents a real time scheduling algorithm that uses DVFS on a mixed task system containing periodic as well as aperiodic tasks on a homogeneous multi-core processor. The proposed algorithm guarantees periodic task deadlines and offers minimum aperiodic task response times. Simulation analysis shows that the proposed scheme saves more energy than cycle conserving, static FVS and non-DVFS scheduling algorithms. Further, it does not result in any response time degradation of aperiodic tasks compared with other algorithms.
    Keywords: dynamic voltage and frequency scaling; real time task scheduling; mixed task set; multi-core processors.

  • Proxy re-designated verifier signature and its applications   Order a copy of this article
    by Haibo Tian, Yufeng Ma, Baodian Wei 
    Abstract: With the development of cloud computing, vast amounts of content are stored in a cloud. Some stored contents may be shared with other people. For a content consumer, it is crucial to identify the owner of some contents. However, for a content owner, it is usually better not to leave evidence on sharing some contents. Considering this requirement, we propose a new cryptographic primitive based on designated verifier signatures (DVS) to enable efficient sharing of sensitive content in a cloud. With the primitive, a content owner can store a sharable content in a cloud. On request from a content consumer, the content owner can produce a re-signing key for a cloud server with which the cloud server produces a customised DVS of the content for the content consumer. The customised DVS can be verified by the consumer, and cannot be transferred to any third party for a proof of source. When the content owner is under investigation, they can always deny their sharing of sensitive contents facing evidence collected from a receiver.
    Keywords: cloud computing; sensitive content sharing; designated verifier.

  • Efficient leakage-resilient blind and partially blind signatures   Order a copy of this article
    by Shuguang Dai, Zhengjun Jiang, Fangguo Zhang 
    Abstract: The techniques of blind and partially blind signatures play an important role in numerous applications, most prominently in electronic voting and electronic cash. In this paper, we first present formal definitions of leakage-resilient blind and partially blind signatures. Subsequently, we propose an efficient leakage-resilient blind signature scheme and an efficient leakage-resilient partially blind signature scheme in the continual leakage model. The proposed leakage-resilient blind signature scheme is the first protocol that is secure even in a setting where the adversary may obtain leakage information on the signer or user's internal state, including secret key and the randomness. However, in the only known leakage-resilient blind signature scheme which was proposed by R"{u}ckert, the adversary is given the leakage information only about the signer's secret key. The proposed partially blind signature scheme is the first leakage-resilient partially blind signature scheme. Also, we analyse their security and efficiency in the generic bilinear group model.
    Keywords: blind signature; partially blind signature; leakage-resilient; bilinear pairings; e-commerce.

  • GO-CP-ABE: group-oriented ciphertext-policy attribute-based encryption   Order a copy of this article
    by Yang Li, Xiaoling Tao, Wei Wu, Joseph K. Liu 
    Abstract: This paper introduces a variant of ciphertext-policy attribute-based encryption called Group-Oriented Ciphertext-Policy Attribute-Based Encryption (GO-CP-ABE). In the new notion, a message is encrypted under an access structure over attributes and users are described by their attributes. In addition, users are divided into different groups and each user belongs to only one group. Users within the same group can merge their attributes to decrypt successfully, if the union of their attributes satisfies the access structure embedded in the ciphertext. But users from different groups can not realise this cooperative decryption. We define the security model of GO-CP-ABE and present an efficient design by revising an existing CP-ABE scheme.
    Keywords: attribute-based encryption; group-oriented; access structure.

  • An autonomous fault-resistant system for mission-critical embedded sensor nodes   Order a copy of this article
    by Hsung-Pin Chang, Tsung-Yu Yeh 
    Abstract: Wireless sensor networks (WSNs) are promising new instruments for monitoring and collecting data about some outside world phenomena. For some mission-critical applications, the WSNs are expected to provide continuous, unattended service for months or even years. However, hardware reliability poses a major challenge to this expectation. Based on a dual-mote architecture, this paper designs and implements an autonomous fault-resistant system. First, a software-based minimal-overhead fault detection method is proposed to detect failures in various hardware components. When a hardware failure is detected, the sensor node lifetime is prolonged by proposing the partial replacement and full replacement fault recovery schemes. Both fault detection and recovery schemes are implemented in the SOS kernel on the mica2 mote. Experimental results indicate that, except for the memory access trap, most failures can be successfully detected through low-cost software detectors. In addition, the fault recovery scheme can choose proper replacement methods for different application modules and successfully increase the lifetime of sensor nodes.
    Keywords: fault management; fault detection; fault recovery; SOS; embedded sensor nodes

  • Fast elliptic curve algorithm using deformed Fibonacci-type series   Order a copy of this article
    by Shuanggen Liu 
    Abstract: The elliptic curve scalar multiplication is the most important operation in elliptic curve cryptography. The efficient and secure scalar multiplication can be constructed by combining the addition chain and elliptic curve. In this paper, we propose an explicit algorithm which is a kind of "double-addition" addition chain based on the Fibonacci type sequence. The "double-addition" sequence of arbitrary integer k is calculated by using the Fibonacci and golden ratio addition chain method. In addition, each cycle of this method is fixed to perform double point and a point add operations, based on the "double-addition" of the elliptic curve scalar multiplication algorithm, so as to be able to resist the simple power attack. At the same time, the length of the chain is greatly shortened by using the double point operation compared with the chain of the Fibonacci. Experimental results showed that the average chain length has attained 38% to 55% reduction compared with other doubling-free addition chain methods.
    Keywords: elliptic curve cryptosystem; scalar multiplication; addition chain; Fibonacci sequence

  • L4eRTL: a robust and secure real-time architecture with L4 microkernel and para-virtualised PSE51 partitions   Order a copy of this article
    by Qingguo Zhou, Rui Zhou, Binbin Yong, Xiaoqiang Wang, Gaofeng Zhang, Hai Jiang, Kuan-Ching Li 
    Abstract: Different classes of applications exhibit different demands on todays heterogeneous computing systems, whose complexity will incur further challenges in ensuring system safety and application security for certain required functionality of these systems. This paper proposes a component-based robust and secure real-time architecture, L4eRTL, which decomposes complex systems into sub-modules and distributes them to POSIX-enabled partitions through para-virtualisation. L4eRTL is designed and implemented based on low-level L4 microkernel and several essential para-virtualised components by IRQ virtualisation, time virtualisation, clock virtualisation, and memory virtualisation. Micro-benchmark programs and sample applications have been conducted to demonstrate the effectiveness of L4eRTL of supporting multiple isolated PSE51 environments for system safety and application security.
    Keywords: para-virtualisation; microkernel; L4; partition; isolation; protection.

  • A dynamic test prioritisation based on DU-chain coverage for regression testing   Order a copy of this article
    by Lili Pan 
    Abstract: Test case prioritisation schedules the test cases for execution in an order that attempts to maximise some objective function or expose faults earlier in testing. Many test case prioritisation techniques have been proposed in the past that prioritise testing cases based on mainly test-requirement coverage and ignore many other testing factors. In view of the DU-chain importance in programs, this paper presents a test case prioritisation approach of method-based DU-chain coverage. The technique combines the DU-chain coverage and fault detection rate as test-case quantitative factors based on method. Different from existing techniques, the new approach makes use of information from executed testing and modules coupling, and dynamically calculates priority quantitative value for every test case. The experiments performed show that the dynamic prioritisation approach is the fault-detection effective,and the APFD of the test suites constructed by the dynamic prioritisation approach is higher than that of the test suites constructed by the static prioritisation technique.
    Keywords: software testing; regression testing; test case prioritisation; DU-chain coverage; class method.

  • Effective traffic signs recognition via kernel PCA network   Order a copy of this article
    by Jianming Zhang, Qianqian Huang, Honglin Wu, Yangchun Liu 
    Abstract: The classification of traffic sign images is easily affected by the change of weather, camera angles, occlusion, etc. The traditional image recognition methods not only require high image quality, but also need to find effective features manually. However, the convolutional neural networks can automatically extract high-level abstract features that are robust to the variations. This paper presents a novel and effective traffic signs recognition approach via the kernel PCA network, based on convolutional neural networks. The kernel PCA network uses a two-layer convolutional network to extract abstract features, and convolution kernels in each layer are directly calculated by the kernel principal component analysis. After nonlinear mapping and pooling, support vector machines are applied to the final classification. The approach can achieve a high recognition rate on the German traffic signs recognition benchmark dataset containing reliable ground-truth data.
    Keywords: kernel PCA network; kernel principal component analysis; German traffic signs recognition benchmark

  • Transportation modes behaviour analysis based on raw GPS dataset   Order a copy of this article
    by Qiuhui Zhu, Min Zhu, Mingzhao Li, Min Fu, Zhibiao Huang, Qihong Gan, Zhenghao Zhou 
    Abstract: Significant information exists in the Global Positioning System (GPS) data for understanding behaviours and transport planning. However, fine-grained identification of transportation modes is still required in the literature. In this paper, we present a robust framework to identify different means of transportation modes from raw GPS datasets. We make the following contributions. (1) We design an effective trajectory segmentation algorithm to divide raw GPS trajectory into single mode segments based on logical assumptions. (2) We propose several modern features, which are more discriminating than traditional features. (3) We adopt an additional segment expansion procedure by considering the whole trajectory. Experiments prove that our framework achieves a promising accuracy for identifying transportation modes.
    Keywords: GPS; transportation mode; random forest classifier.

  • A novel cognitive radio spectrum allocation scheme with chaotic gravitational search algorithm   Order a copy of this article
    by Lin Guo, Zhigang Chen 
    Abstract: Cognitive Radio (CR) is a promising solution to the lack of spectrum, as well as spectrum inefficiency, in current communication networks. A major demand of this technology is for efficient and fair spectrum assignment to unlicensed (secondary) users. This paper presented a novel method to address this challenge in CR networks, based on the Graph Coloring Problem (GCP) and Gravitational Search Algorithm (GSA). In addition, the chaotic search process has been designed in the method to avoid falling into local optimum. Last, we compare the performance of the proposed algorithm with Particle Swarm Optimisation (PSO), Genetic Algorithms (GA) and Quantum Genetic Algorithm (QGA ).
    Keywords: cognitive radio system; spectrum allocation; gravitation search algorithm; chaotic search

  • Dynamic frequency scaling for embedded systems with memory-intensive applications   Order a copy of this article
    by Hyoungjong Kim, Moonju Park 
    Abstract: Power management of embedded systems is an important issue as they are typically powered from limited energy storage. To reduce the power consumption of the CPU, which is the most power-consuming device when the system is actively running, a dynamic frequency/voltage scaling (DFS) technique has been used widely and become essential in embedded systems. DFS techniques use various information, such as CPU utilisation, the number of ready threads, and/or cache miss rate. In this paper, we consider the cycles per instruction (CPI) as the primary indicator of energy efficiency in relation to the CPU frequency. By testing and analysing applications characteristics on a real target hardware, we observe that memory access affects the CPI, and found that higher CPI lowers the energy efficiency and performance gain we can get by frequency scale-up. Based on the observation, we propose a new DFS algorithm that monitors the CPI value to determine the CPU frequency. Experimental results show that the proposed DFS algorithm provides higher energy efficiency for memory-intensive application; it reduces the energy consumption by about 28.6%, without causing delay in execution. The proposed algorithm is designed to consider the effect of memory access for more efficient support of memory-intensive applications, but it works well with CPU-intensive application and mixed type of application also.
    Keywords: dynamic frequency scaling; embedded system; scheduling

  • A hardware in the loop emulator for a satellite control system   Order a copy of this article
    by Mokhtar Aboelaze, Mohamed Shehata, Sumaia Atiwa 
    Abstract: Design and testing of algorithms for satellite attitude control is not an easy task. Once the system is deployed (the satellite is launched) there is no room for error or system modifications. That, of course, requires extensive testing and simulation before deployment. However, simulation can not capture all aspects of system operation. For example, capturing jitter in the system due to hardware issues such as cache miss, interrupts, dynamic scheduling, or instruction prediction is almost impossible. In such a case, a hardware in the loop (HiL) simulation platform is used to capture real-time system behaviour. In this paper, we propose and implement an HiL simulator for a small satellite on FPGA. The model implements the satellite dynamics as well as jitter and noise added to the signal. We use our emulator to study the effect of fixed point implementation on the controller performance. Our results indicates that we can achieve a 50% power saving using fixed point implementation (as compared to floating point implementation) with almost no performance degradation. We also use the HiL platform to test the effect of noise and jitter on the system performance.
    Keywords: hardware in the loop; satellite attitude control; FPGA; variable structure control.

  • Multi-core model checking and maximum satisfiability applied to hardware-software partitioning   Order a copy of this article
    by Alessandro Trindade, Renato Degelo, Edilson Galvão, Hussama Ismail, Helder Silva, Lucas Cordeiro 
    Abstract: Bounded Model Checking (BMC) based on Satisfiability Modulo Theories (SMT) is well known by its capability to verify software. However, its use as an optimisation tool, to solve hardware and software (HW-SW) partitioning problems, is something new. In particular, its integration with the maximum satisfiability solver vZ tool, which provides a portfolio of approaches for solving linear optimisation problems over SMT formulas, is unprecedented. We present new alternative approaches to solve the HW-SW partitioning problem. First, we use SMT-based BMC in conjunction with a multi-core support using open multi-processing to create four variants to solve the partitioning problem. The multi-core SMT-based BMC approaches allow initialising many verification instances based on the number of available processing cores, where each instance checks a different optimum value until the optimisation problem is satisfied. Additionally, we integrate the vZ into the BMC, making it as a specialised solution for optimisation in a single-core environment. We implement all five approaches on top of the Efficient SMT-Based Context-Bounded Model Checker (ESBMC) and compare them with a state-of-the-art optimization tool. Experimental results show that there is no single optimisation tool to solve all HW-SW partitioning benchmarks, but based on medium-size benchmarks, ESBMC-vZ had better performance.
    Keywords: hardware-software co-design; hardware-software partitioning; optimization; model checking; multi-core; maximum satisfiability.

  • A study of IP-based vehicular gateway with IPv6   Order a copy of this article
    by He Yu, Guihe Qin, Minghui Sun, Xin Yan, Xingchen Wu 
    Abstract: With the progress of ambient sensor networks (ASNs), there is a trend that each node in ASNs should gather information and a server will supply intelligent service for users by processing and analysing the information. In order to achieve this purpose, each node and server must communicate with each other freely. IPv6 lets any host generate unique IP address and supplies far more addresses than IPv4. Therefore, it is necessary to migrate the IP address of each node from IPv4 to IPv6. As a proof-of-concept, we use the vehicle as an example. We propose the design and implementation of an IPv6-based In-Vehicle Gateway (IVG), and achieve end-to-end access between IPv6-based CAN (Controller Area Network) unit and Ethernet. We use tunnel technology to solve the issue through IPv4 to IPv6, develop address mapping method, and implement this notion in a prototype vehicle.
    Keywords: controller area network; IPv4-to-IPv6 tunnel; in-vehicle gateway; heterogeneous network.

  • Generating verifiable LOTOS specifications from UML models: a graph transformation based approach   Order a copy of this article
    by Salim Djaaboub, Elhillali Kerkouche, Allaoua Chaoui 
    Abstract: The increasing complexity and widespread use of complex and critical systems requires advanced techniques and tools to address their specification, verification and validation. The goal of this paper is to integrate two standard languages (UML and LOTOS) for the specification, verification and validation of dynamic behaviours of critical systems. The main purpose of this integration is to take benefits of the ease-of-use of the graphical notation of UML in system modelling and the formal notation of LOTOS in system verification. In this paper, we propose a graph transformation based approach to generate automatically LOTOS specifications from UML dynamic models. This approach enables developers on the one hand to model the behaviours of systems using graphical UML statechart and communication diagrams, and on the other hand to generate automatically verifiable LOTOS specifications. The proposed approach is automated using AToM3 tool, and it is illustrated through the modelling and verification of two embedded systems.
    Keywords: UML; LOTOS; statechart diagram; communication diagram; critical systems; formal methods; verification; graph transformation; AToM3.

  • Multiple features fusion for facial expression recognition based on ELM   Order a copy of this article
    by Lingzhi Yang, Xiaojuan Ban, Yitong Li, Guang Yang 
    Abstract: Traditional facial expression recognition includes a feature extractor and a classifier. In this paper, a multiple features fusion approach for facial expression recognition is proposed to improve the recognition accuracy. We consider a feature level fusion method, serial feature fusion, and decision level fusion, linear opinion pool, to combine multiple features. Local binary patterns, local directional number pattern and edge orientation histograms are used to extract features. Then, extreme learning machine is used as the classifier for expression classification. Experiments on JAFFE and CK+ show the method achieves better results.
    Keywords: facial expression recognition; feature extraction; extreme learning machine; multiple features fusion.

  • Research of dynamic load balancing based on stimulated annealing algorithm   Order a copy of this article
    by Huyin Zhang, Kan Wang 
    Abstract: This article analyses the advantages and shortcomings of classical load balancing algorithms based on dynamic feedback on a server cluster, and combined stimulated annealing with this strategy to put forward an optimised model of dynamic load balancing. This model uses the stimulated annealing algorithm to calculate accurate performance parameters of load information on every service node, then estimates the actual load of nodes by dynamic feedback, in order to ensure a reasonable distribution of tasks. Experimental results show that in the case of a large amount of requests, this algorithm, in comparison with classical load balancing strategy of dynamic feedback, can effectively reduce the response time of tasks and ensure high throughput, which could improve the whole system performance.
    Keywords: server cluster; load balancing; dynamic feed-back; stimulated annealing; optimisation.

  • Differential-linear cryptanalysis of Simon32/64   Order a copy of this article
    by Yanqin Chen, Wenying Zhang 
    Abstract: Simon is a family of lightweight block ciphers designed by the US National Security Agency in 2013. Simon 2n/k is a cipher in this family with k-bit key and 2n-bit block. So far, there have been several cryptanalytic results on this cipher by means of differential cryptanalysis, linear cryptanalysis and impossible differential cryptanalysis. In this paper, we improve the previous linear cryptanalysis by differential-linear cryptanalysis, which is based on the use of a differential-linear distinguisher constructed by concatenating a linear approximation with a differential. The number of attacks is not increased, but the time complexity of attack on 18-round Simon32 is reduced from 2^{32} to 2^{19}. In addition, we present a key recovery attack on 18 and 19 rounds of Simon32 based on differential-linear distinguisher.
    Keywords: Simon block cipher; differential cryptanalysis; linear cryptanalysis; differential-linear cryptanalysis.

  • Efficient VLR group signatures for smart cards   Order a copy of this article
    by Kamil Kluczniak, Lucjan Hanzlik, Jianfeng Wang 
    Abstract: Group signatures are signature schemes that reveal only the group membership information of the signer. Verifier local revocation group signatures are group signatures that do not require the signer to update his secret key in order to provide revocation in the group. In this paper, we design a practical verifier local revocation group signature based on bilinear maps. Our scheme is the first VLR group signature using pairings that does not require expensive operations done by a signer, such as exponentiation in the target group or pairing evaluation. This makes our signature scheme especially suitable for implementation on devices with restricted resources, such as smart cards.
    Keywords: VLR group signatures; smart cards; resource restricted hardware; strong Diffie-Hellman assumption; revocation.

  • Mechanical amelioration to improve hexapod robot speed   Order a copy of this article
    by Long Gao, Jianping Yin, En Zhu, Tianhang Liu, Wei Chen, Minghui Qiu 
    Abstract: This paper describes the design and simulation of crab-like hexapod robot. Mechanical amelioration and new lateral walking gait were designed to improve the speed and obstacle-crossing ability of the robot. The legs were designed with variable length claws, which were constructed to study the influence of leg length on robot performance. Through simulation and feasibility-checking processes, the lengths of the legs were optimised. The test results proved that the crab-like robot performs better than the straight-walk robot in speed and obstacle-climbing ability.
    Keywords: crab-like robot; speed; simulation; prototype.

  • A lightweight and efficient encryption scheme based on LFSR   Order a copy of this article
    by Guangfu Wu, Keke Wang, Jinjun Zhang, Jiguang He 
    Abstract: Privacy and trust in wireless networks have attracted plenty of attention in the information age. Various types of high-complexity encrypt algorithm are exploited for improving the security of the communication, such as providing security in Global System for Mobile communication (GSM) cell phones. This paper proposes a new algorithm, which combines the Vigen
    Keywords: Vigenère cipher; encryption; decryption; linear feedback shift register.

  • Electric power communication bandwidth prediction based on adaptive extreme learning machine   Order a copy of this article
    by Li Di, Zheng Zheng, Song Wang, Ruidong Zhang, Min Xia, Kai Hu 
    Abstract: Bandwidth demand forecasting is the basis and foundation of power communication network planning. For the traditional neural network learning, there are many problems, such as slow convergence speed, more iterative times, and easy to fall into local optimum. An adaptive extreme learning machine model based on the theory of extreme learning machine and K nearest neighbour theory is proposed to predict the bandwidth of electric power communication. The adaptive metrics of inputs can solve the problems of amplitude changing and trend determination, and reduce the effect of the over-fitting of networks. The proposed algorithms are validated using real data of a province in China. The results show that this method is better than the traditional neural network, auto-regressive models, self-organisation models, and single extreme learning machine model. It can be used in electric power communication bandwidth prediction.
    Keywords: electric power communication; bandwidth prediction; extreme learning machine; K nearest neighbours.

  • Spatial descriptor embedding for near-duplicate image retrieval   Order a copy of this article
    by Yunlong Wang, Zhili Zhou 
    Abstract: The existing methods for near-duplicate image retrieval are mostly dependent on the bag-of-words (BOW) model. However, the procedure of quantisation leads to the low discrimination of visual words, causing many false local matches. In this paper, we propose a novel spatial descriptor embedding method for near-duplicate image retrieval, which encodes the relationship of the SIFT dominant orientation and the exact spatial position between local features and their context to be spatial descriptors, and then embeds them in the index to improve the distinctiveness of visual words. Moreover, a secondary matching structure for spatial descriptors matching is used to effectively and efficiently implement the near-duplicate image retrieval. Experimental results on Copydays illustrate that our method achieves superior performance to the state-of-the-art methods.
    Keywords: near-duplicate; bag-of-words; spatial descriptor embedding.

  • A method for electric load data verification and repair in home environment   Order a copy of this article
    by Qi Liu, Shengjun Li, Xiaodong Liu, Nigel Linge 
    Abstract: Home energy management (HEM) and smart home have become popular. HEM collects and analyses the electric load data to make the power use safe, reliable, economical, efficient and environmentally friendly. Without the correct data, the correct decisions and plans could not be made, so the data quality is of great importance. This paper focuses on the verification and repair of the electric load data in a family home environment. Owing to the irregularity of modern peoples lifestyles, this paper proposes a system of N + 1 framework to handle this properly. It collected every appliances information and the power buss information to make them verify each other, so it can solve the stochastic uncertainty problem and verify if the data is correct or not to ensure the datas quality. During data upload, there are many factors such as smart meter malfunctions, communication failures, which will cause some wrong data. To repair the wrong data, a proposed method called LBboosting integrates two curve-fitting methods. As the results show, the method has a better performance than up-to-date methods.
    Keywords: data verify; data repair; load data quality; power systems; home energy management.

  • Traffic flow detection method based on vertical virtual road Induction Line   Order a copy of this article
    by Jieren Cheng 
    Abstract: Traffic flow detection is an important part of an intelligent transportation system and it has a wide range of applications. We analyse the existing methods of traffic flow detection and propose a traffic flow detection method based on vertical virtual road induction line (VVRIL). Firstly, according to the direction of vehicle travel, we set a VVRIL in the middle of the driveway. Secondly, the background image is gained from the video image with a Gaussian mixture model. We then make differential operation between the background image and video image to get a binary image, in which we set the values of the foreground pixels as 1 and that of background pixels as 0. Thirdly, we extract the values of the pixels in the VVRIL of the binary image. Besides, we regard the vehicle maximum length obtained by self-learning as the length of the detection zone and get the information of vehicles in the VVRIL. Finally, we get the number of vehicles through the analysis of vehicle centre coordinates in the VVRIL of each video image. Experimental and theoretical analyses show that the method is accurate enough to meet the requirement of real-time performance.
    Keywords: road induction line; traffic flow detection; self-learning; Gaussian mixture model.

  • Router-shared-pair mesh: a reconfigurable fault-tolerant network-on-chip architecture   Order a copy of this article
    by YaLi Chen, Kaixin Ren, Naijie Gu 
    Abstract: This paper proposes a fault-tolerant scheme on a network-on-chip-based system-on-chip (NoC-based SoC), for problems of isolated processing element (PE) and parted regions caused by permanent faults. The scheme is referred to as router-shared-pair mesh (RSPmesh). The topology architecture of the RSPmesh uses the design that a pair of neighbouring PEs share a pair of routers, and uses MUXs to provide diversity for link-connections between routers. A topology reconfiguration algorithm and a routing algorithm corresponding to the RSPmesh are also proposed. Thus, when there are faulty routers or links, RSPmesh-based NoC can be reconfigured to a new 2D mesh NoC with maybe smaller size, but regular and with no faults, and it is able to serve all healthy PEs. The RSPmesh uses no spare routers, and only makes several routers disable according to actual needs in topology reconfiguration. Evaluation and experimental results show that the proposed scheme achieves significant improvements in reliability.
    Keywords: network-on-chip; fault tolerant; isolated PE problem; parted regions problem; topology reconfiguration; 2D mesh; router-shared-pair mesh.

  • Application source code modification for processor architecture lifetime improvement   Order a copy of this article
    by Montassar Ben Saad, Ahmed Jedidi, Smail Niar, Mohammed Abid 
    Abstract: In the optimal functioning of SoCs, two significant metrics of quality are the most important: lifetime and reliability. This paper focuses on methods to increase the lifetime of a processor. Two methods are presented: Relax Point Injection (RPI) and Code Structure Adaptation (CSA). In RPI, a specific treatment is incorporated into the application code to prevent a harmful rise in the temperature of the chip. The MTTF of the processor is increased by 33.88% through means of an RPI method. However, the execution time of the application is sometimes increased by the RPI by more than 12%. In the CSA method, the arrangement of the application code is regulated to improve the lifetime of the processor. The MTTF of the processor is increased up to 28% by the CSA technique and the implementation time is maintained.
    Keywords: mean time to failure; thermal dissipation; relax point injection; code structure adaptation.

  • Iterative algorithms for impulsive noise reduction in OFDM-based power line communications   Order a copy of this article
    by Samir Laksir, Abdelaali Chaoub 
    Abstract: Power Line Communications (PLC) is a technology that permits data transmission using electrical networks. In the last few years, multimedia transmission (e.g. audio, image and video) over electrical signals has received a huge amount of research interest thanks to the already-existing indoor networks. However, impulsive noise presents the most impairments in PLC systems caused by switching transients in the in-home networking. In this paper, we propose some iterative suppression algorithms based on accurate impulsive noise estimation, using an adaptive threshold under a target false alarm probability. The proposed algorithms detect the amplitudes of impulsive noise, and then cancel them iteratively from the received contaminated signal. The results show that the proposed algorithms provide noticeable improvement in terms of bit error rate, peak signal-to-noise ratio, and visual reconstructed image quality, when compared to that of the conventional methods.
    Keywords: power line communications; orthogonal frequency division multiplexing; multimedia transmission; impulsive noise; iterative suppression algorithms; false alarm probability; impulsive noise estimation; bit error rate; peak signal-to-noise ratio; visual image quality.

  • A new scheme for improving the utilisation of nested-cloud resources   Order a copy of this article
    by Yuan Ni, Zhiwei Zhang 
    Abstract: In recent years, cloud computing has played an important role in IT fields. It brings benefits such as high computing efficiency, cost saving, provisioning on-demand of computing resources and high utilisation of the hardware. However, with more fields and business cloud computing involved, the inherent problems in its structure are restricting the further development of cloud computing. The most serious problem is how to achieve the highest usage of the cloud resources. In this paper, we present a scheme based on multi-layer nested virtualisation. It can make full use of the allocations of a virtual machine provided by an Infrastructure-as-a-Service (IaaS) provider. Furthermore, we also propose a corresponding task scheduling algorithm for the nested cloud environment. The task scheduling considers both the computing efficiency and the monetary cost paid for the cloud service. In order to justify our proposal, we use KVM as unmodified multiple hypervisors to run multi-layer VMs on x86 platform. We also do simulations to test our task scheduling algorithm. The result shows encouraging support for our proposal.
    Keywords: cloud architecture; multi-layer nested virtualisation; task scheduling; KVM; Intel-VT.

  • A provably secure delegated authentication scheme and its applications   Order a copy of this article
    by Qun Lin, Jianzhong Li, Xuechang Ren 
    Abstract: In a proxy signature scheme, an original signer can delegate his/her signing capability to a proxy signer, so that the proxy signer can sign on behalf of the original signer. Proxy signature is an important technology in delegated authentication scheme, so it is important to design provably secure proxy signature schemes. In 2012, Boldyreva et a1. gave the definition of proxy signature and formalised a model of security for proxy signature schemes. They not only formalised a model of security for proxy signature schemes, but also specified the adversary's capabilities and goals. In this paper, we propose a new provably secure proxy signature scheme under this model, which is more efficient than that of the existing ones. Furthermore, we use this signature scheme to construct a proxy blind signature scheme, and give the security analysis of the new scheme. Proxy blind signature can be applied in cloud computing.
    Keywords: proxy signature; provable security; proxy blind signature; cloud computing.

  • Region-based trilateral filter for depth video coding   Order a copy of this article
    by Chunyue Hu 
    Abstract: 3D video systems using depth-image-based rendering (DIBR) are attracting significant interest because of their low processing cost. In order to enable these systems, the depth video must be coded in addition to the texture video. During the coding process, coding artifacts in the depth map could cause video quality degradation of virtual view. In this paper, a region-based trilateral filter for depth video coding is proposed to improve the coding quality. First, the depth map is split into multiple objects with the label of segmentation. Then, in order to remove the artifacts from different objects and preserve the sharp edge, each pixel is filtered by using neighboring pixels belong to the same object. The proposed method has been evaluated with several 3D video sequences in HEVC platform. Experimental results demonstrate that the rendering quality can achieve a considerable gain under the same bitrate.
    Keywords: 3D video; HEVC; depth video coding; trilateral filter.

  • Can finger knuckle patterns help to strengthen e-banking security?   Order a copy of this article
    by Abdallah Meraoumia, Djamel Samai, Salim Chitroub 
    Abstract: Communication via the internet has become vital for any kind of information exchange, private, public, commercial, or military. Banks are the first that have used the internet for financial transactions (e-banking). However, the safe use of e-banking implies that all precautions have been considered to identify legitimate users and thus avoid economic and social damage that may be caused by any possible fraud. In this context, we propose in this paper a secure biometric system dedicated to e-banking for reducing the fraud risk and strengthening the customer confidence. The fuzzy commitment concept associated with the Finger-Knuckle-Print (FKP) is the core of our proposed system. However, such a system will only be efficient if the FKP features are accurately extracted. For this, we have developed a new method of feature extraction called Adaptive Extended Binary Pattern (AELBP). The obtained experimental results have been judged promising for a high security of e-banking with guaranteed trust from costumers.
    Keywords: information security; cryptography; fuzzy commitment; biometrics; finger-knuckle-print; feature extraction; local binary pattern; data fusion.

  • Interactive map matching and its visualisation: techniques and system   Order a copy of this article
    by Li Cai, Bingyu Zhu, Yifeng Luo, Shuigeng Zhou 
    Abstract: The trajectory data of taxis is an important kind of traffic data. Many traffic applications need to perform processing and analysis on trajectory data. Visualising trajectory data of vehicles on road maps is an important measure of reflecting and demonstrating the trend of traffic variation, where map matching from trajectory data to the road network plays the most crucial role in such a visualisation process. We design and implement a novel interactive visualised map matching system in this paper, namely MMatchingVis, which provides multiple front-end functions including road selection, data extraction, map matching algorithm selection, and result display, based on web techniques and Baidu Map. MMatchingVis employs the JStorm platform for trajectory data processing. We evaluate MMatchingVis' map matching results with the trajectory dataset collected from 6599 taxis in Kunming, and evaluation results show that MMatchingVis could efficiently process and analyse trajectory data, support multiple user interaction models, and provide fine-grained visualisation presentation.
    Keywords: visualisation; map matching; GPS trajectories data; user interaction; cloud computing.

  • Sign prediction and community detection in directed signed networks based on random walk theory   Order a copy of this article
    by Baofang Hu, Hong Wang, Yuanjie Zheng 
    Abstract: Previous studies on social networks often focused on networks with only positive edges between node pairs. As a significant extension, we applied the random walk theory based on graphs with both positive and negative edges. In particular, we derived the commute time similarity between node pairs in directed signed networks and proved that its corresponding Laplace spectral was a legal kernel to compute the similarities between node pairs. We used the similarity distance to predict the sign and direction of the edges on two real social networks based on the idea of collaborative filtering, and the experimental results showed that the method provided good performance. We also used the defined Laplacian spectrum of the directed signed networks to detect the community structure in two real-world networks and three synthetic networks, and the algorithm achieved good performance.
    Keywords: directed signed network; random walk; community detection; sign prediction; collaborative filtering.

  • Handling startling circumstances with IRM scheduler of real-time systems   Order a copy of this article
    by Mahmoud Naghibzadeh 
    Abstract: There are many vital real-time systems, such as avionics, mission-critical, industrial control, and space missions, which cannot tolerate any request overruns. Safeness analysis of such systems is directly dependent on the scheduling strategy being used. Rate-monotonic and earliest deadline first are the leading scheduling strategies for these systems. Before deployment, it is essential to make sure no task misses occur for such hard real-time systems. This is usually done by formally proving the safeness of the system for the given set of tasks. Besides, a scheduler is preferred which performs better in unexpected situations, such as when a transient fault occurs. The purpose of this paper is to first reveal some new behaviours of the intelligent rate-monotonic scheduler and then evaluate its performance in unexpected situations. Simulation results show that it performs better than both rate-monotonic and earliest deadline first in such situations.
    Keywords: scheduling; intelligent rate-monotonic; pre-emption; deadline miss.

  • A practical approach for estimating human daily water intake   Order a copy of this article
    by Bin Dai, Rung-Ching Chen, Yuan-Yu Ding 
    Abstract: The proportion of water in the human body must keep in a proper level to maintain normal physiological action. Daily water consumption needs to be properly supplemented in time to protect the health of human beings. Water consumption is related to age, body weight, temperature, physical activity, etc. These factors are generally difficult to express with crisp data, and it is not easy to get accurate values of recommended daily water intake. The main objective of this paper is to build a recommended daily water intake system and a practical application using fuzzy reasoning methods. We also compared the actual recommended values with our system output values to find the differences. We have designed an application on the Arduino platform and use Bluetooth electronic scale to connect to smart phones to help people to control their daily water intake. The experiment results proved that the recommendation system is effective in actual applications.
    Keywords: recommendation system; daily water intake; fuzzy system; Arduino; electronic scale.

  • Efficient authentication scheme for vehicular ad-hoc networks with batch verification using bilinear pairings   Order a copy of this article
    by Hang Tu, Cui Jingsong 
    Abstract: The potential for vehicular ad hoc networks (VANETs) in improving traffic, enhancing road safety and reducing traffic accidents has attracted attention from academia, industry, and governments. To ensure secure communication in VANETs, a number of authentication schemes, including those with batch verification, were proposed in recent years. However, studies have demonstrated that most of the existing schemes suffer from bad performance or weak security. To address those problems, we construct a new identity-based digital signature (IBDS) scheme using bilinear pairings. The IBDS scheme is then used to construct a new identity-based conditional privacy-preserving authentication (IBCPPA) scheme for VANETs without the need for a map-to-point hash function or double secret keys. Using simulations, we demonstrate that our provably-secure IBCPPA scheme not only achieves better performance than related schemes, but also overcomes the inefficiency problem of the double secret keys in related schemes (i.e. the system does have to manage two secret keys to provide security).
    Keywords: authentication; vehicular ad-hoc networks; security; bilinear pairing.

  • A new efficient privacy-preserving data publish-subscribe scheme   Order a copy of this article
    by Ping Chen, Zhiying Wang, Xiaoling Tao 
    Abstract: Data publish-subscribe is an efficient service for users to share and receive data selectively. Owing to the powerful computing resources and storage capacity, the cloud platform is considered as the most appropriate choice to publish and subscribe large-scale data generated in real-world life. However, the cloud platform may be curious about the content of published data and subscribers' interests. In this paper, we aimed at realising a secure and efficient privacy-preserving data publish-subscribe scheme on cloud platforms. On one hand, we adopt ciphertext-policy attribute-based encryption (CP-ABE) to encrypt the data based on its access policy. Moreover, part of the decryption computation is shifted to the cloud platform to reduce subscribers' computation overhead. On the other hand, we use an efficient searchable encryption scheme based on bloom filter tree (BFtree) to protect subscribers' privacy and match their interests with encrypted data. Not only that, publishers and subscribers can also exchange their roles in our scheme. The security analysis and experimental results prove that our scheme is efficient and secure in privacy-preserving data publish-subscribe service.
    Keywords: privacy-preserving; data publish-subscribe; CP-ABE; BFtree; cloud platform.

Special Issue on: MCSoC-13 Embedded Multicore and Many-Core Architectures

  • Architecture and design of real-time system for elderly health monitoring   Order a copy of this article
    by Achraf Ben Ahmed, Abderazek Ben Abdallah 
    Abstract: Despite the decreased human mortality rate, heart disorders are one of the main causes of death around the world. As a result, detection of irregularities in the rhythms of the heart is a growing concern in medical researches. The collection, processing, and visualisation of such biomedical data in real-time is a challenging task owing to the large amounts of data that need to be processed, especially when the records are made for a long time. Recent technological advances in sensors and low-power microelectronics have enabled the development of a single embedded biomedical chip capable of running computationally intensive biomedical applications, such as remote analysis and monitoring of human heart activity, which is still a challenging problem for biomedical engineers. In this work, we present a novel architecture and hardware/software prototyping of a real-time system, targeted for elderly health monitoring, named BANSMOM. The proposed system achieves its real-time performance via parallel processing techniques and a Period-Peak-Detection algorithm (PPD) for processing multi-lead electrocardiography records in parallel. We tested the proposed system with real ECG fixed length records (10s/sample) from the MIT database. From the evaluation results, we found that the system meets its real-time requirements and achieves about 69% accuracy.
    Keywords: multi-core system-on-chip; real-time monitoring; hardware/software prototyping; parallel processing.

Special Issue on: ICESC 2014 Electronic System Design and Computational Intelligence

  • A novel filter algorithm for impulse noise removal from digital images in a library database system   Order a copy of this article
    by Yaqin Li, Lan Qiu, Cao Yuan 
    Abstract: Library database systems are generated from a lot of online images. They are stored in databases that grow massively and become difficult to capture, form, store, manage, share, analysse and visualise via typical database software tools. In this paper, a switching median and morphological filter is presented for removing impulse noise. The noise detector is first adopted to identify noise pixels by combining the morphological gradient based on the erosion and dilation operators with the top-hat transform. Then the detected impulses are removed by the hybrid filter, which combines the improved median filter using only the noise-free pixels with the conditional morphological filter using the improved morphological operations. The results of simulations demonstrate that the proposed filter can realise accurate noise detection, and it has significantly better restoration performance than a number of decision-based filters at the various noise ratios.
    Keywords: impulse noise; noise detector; median filter; morphological filter.

Special Issue on: IJES New Scopes in Embedded Computing

  • Creating recommendations in an energy-efficient and safety relevant driving system while considering driver stress and driver reaction   Order a copy of this article
    by Emre Yay, Natividad Martínez Madrid 
    Abstract: Because saving energy and road safety have become very important in recent decades, several driving assistance systems have been developed that help to improve driving behaviour. However, these driving systems cover either the area of energy-efficiency or safety. Furthermore, they do not consider the reaction of the driver to a shown recommendation and the driver stress level. In this paper, the decision process of showing a recommendation to the driver in an energy-efficient and safety-relevant driving system is presented. The decision process considers the driver reaction to a shown recommendation and the driver stress in order to increase the user acceptance and the road safety. The results of the evaluation showed that the driving system was able show recommendations when needed, while suppressing recommendations when the driver ignored a recommendation repeatedly or when the driver was in stress.
    Keywords: energy-efficiency; safety; advanced driver assistance systems; stress detection; driving behaviour.

  • Different soft computing algorithms used in fire sensor node of a wireless sensor network integrated with IoT   Order a copy of this article
    by S.R. Vijayalakshmi, S. Muruganand 
    Abstract: The Internet of Things (IoT) concept is a promising new pattern for future internet development. Wireless Sensor Networks (WSNs) are visualised as an integral part of unpredictable IoTs. There are the potentially huge number of cooperating IoTs that are usually used in the monitoring and management of real world phenomena. The reliability of individual sensor nodes, the overall environmental monitoring and improvement of sensor networks are definitely challenging issues. One of the most interesting real world phenomena that can be monitored by WSN is fire. Soft computing technology such as fuzzy logic, DS algorithm using Dempster-Shaffer theory, comparison algorithm and threshold algorithm are incorporated in sensor nodes in order to make the sensor network manageable, with environment monitoring and control of the environment. Selecting the best soft computing technique for the sensor node is useful in the maximum extension of a component's life-cycle and the best design of sensor nodes. Many aspects, such as energy efficiency, coverage, cost of the system, prediction of fire and Quality of Services (QoS) have been analysed. The node uses a digital temperaturehumidity sensor, light sensor, smoke detector for measurement and MSP430 microcontroller for processing and implementing for fire detection. The detected information is transmitted to the work station through XBeepro for short distance wirelessly. From the workstation it is connected throughout the world through the internet.
    Keywords: fire protection, fuzzy logic, wireless sensor networks, Internet of Things, temperature sensor, DS algorithm, security systems, threshold algorithm to detect fire, sensor node.

  • Eye blinks artifacts detection in a single EEG channel   Order a copy of this article
    by Amin Zammouri, Abdelaziz Ait Moussa 
    Abstract: In electroencephalography (EEG), the appearance of electrical disturbances in the brain signal represents a major obstacle in the scientific interpretation of the signal. In clinical conditions, the EEG measurements are mainly influenced by muscles and ocular movements, especially eye blinks. In this work, we present a new method to detect and reject eye blinks from a single-channel EEG signal. Of an offline use mode, the proposed approach is based on statistical computations. The detection algorithm first aims at estimating the pure EEG data interval, and second, we seek to improve the errors that may occur during the first step by using the Fisher-Snedecor test. This test is applied to a reference eye blink, which is computed for each subject. By using ROC performance metrics, kappa coefficient and Signal-to-Artifact Ratio (SAR), the proposed method is compared with an expert detection and with Single-Channel Independent Component Analysis (SC-ICA), one of the widely used and robust methods for artifact rejection. Experimental results show large values, even when using the experts annotation and the comparison with the SC-ICA method. This reflects the efficiency of the proposed method in detecting and rejecting blinks from a single-channel EEG signal.
    Keywords: ocular artifact; eye blink; brain signal; single-channel; EEG.

  • Accident prevention and prescription by analysis of vehicle and driver behaviour   Order a copy of this article
    by Shriram K Vasudevan, Mathews Peter 
    Abstract: Vehicle acceleration, when analysed against location, gives those locations where there are more sudden accelerations and decelerations. Lateral acceleration of a vehicle when analysed against the driver identity can reveal if the driver is rash or not, assuming a driver is rash if there are more incidents of sudden steering movements. Upon identification of the acceleration and location data, they are stored against driver ID. A set of algorithms are proposed in the paper, and are implemented to predict accidents. Other implementations include alerting the driver if an accident is predicted, and also recording and saving audio and visuals if an accident is detected.
    Keywords: vehicle acceleration; vehicle deceleration; vehicle accident; vehicle; location ; driver behaviour; steering; android; arduino; pattern; prediction.

  • Implementation of a reliable mechanism for protecting IP cores on low-end FPGA devices   Order a copy of this article
    by Mario Barbareschi 
    Abstract: As field programmable gate array (FPGA) technology is being adopted in many digital systems, the demand for security increases, especially when intrinsic vulnerabilities of programmable devices jeopardise the intellectual properties (IPs). New high- and medium-end FPGA devices have built-in mechanisms that, exploiting AES primitives, are able to avoid IP piracy by preventing cloning and reverse engineering, but the low-end FPGA families still lack security solutions. Recently, in the literature, a great research effort has been done on Physically Unclonable Functions (PUFs), which are eligible to be a fundamental means for authenticating integrated circuits. They can be adopted to guarantee protection against IP violations by implementing a locking Finite State Machine (FSM) on any device. In this paper, we show two implementations of the Anderson PUF, a good scalable and high reliable PUF architecture, on the Xilinx Spartan-3E family, which can be adopted to introduce the locking mechanism. In the experimental result we show the quality parameters for signatures generated.
    Keywords: IP protection, FPGA security, physically unclonable functions, fuzzy extractor, Anderson PUF, Xilinx Spartan-3E

  • Designing an SRAM PUF-based secret extractor for resources-constrained devices   Order a copy of this article
    by Mario Barbareschi 
    Abstract: Extracting binary secrets from the unique physical imperfections, which affect every manufactured silicon device, guarantees attractive properties such as randomness, physical unclonability and tamper evidence. Instead of involving non-volatile memory as storage, Physically Unclonable Functions (PUFs) are able to provide keys from physically imprinted secrecy. However, the implementation of such a promising solution has to cope with unstable values provided by the PUF, requesting post-processing techniques to recover the secret from a noisy version. One of the most interesting PUF architectures exploits the pattern generated by static RAM cells when being powered up, because many circuits embed them as non-volatile memory technology. Nevertheless, owing to overheads introduced by the secret recovering, even if the SRAM is available to be used as a PUF on a device, the design of a secret extraction architecture must take into account the availability of requested computational resources. In this paper, we review one of the main techniques that accomplishes the secret extraction from SRAM PUFs, namely the fuzzy extraction algorithm, detailing involved tools and design parameters for an implementation on a commercial device. For this purpose, we target the STM32F4 microcontroller family, tailoring every design parameter for the SRAM embedded in it, and demonstrating the feasibility of the approach with an application based on the remote secure software update.
    Keywords: SRAM; microcontroller; physically unclonable functions; fuzzy extractor.

Special Issue on: Data Management and Intelligent Application for the Internet of Things

  • Time synchronisation attacks and defences in IEEE802.15.4e networks   Order a copy of this article
    by Wei Yang, Qin Wang, Yadong Wan, Yue Qi 
    Abstract: Time synchronisation is very crucial in many wireless sensor network applications, especially in industrial wireless networks. The current industrial wireless standards all use TDMA-based channel-sharing protocols on the Medium Access Control (MAC) layer. If an adversary launches time synchronisation attacks to an industrial wireless network, the whole network's communication will be paralysed. However, the time synchronisation is not insufficient to be protected in the current industrial wireless standards, which are based on the IEEE802.15.4e standard. So it is important to study in depth the time synchronisation method of attack and defence in IEEE802.15.4e networks. In this paper we give a survey of time synchronisation in IEEE802.15.4e networks and point out the possible attacks. These include ASN attack, message manipulation attack, node identity attack and pulse-delay attack. Then we propose some countermeasures against these attacks. Finally, we perform a series of experiments to evaluate the effectiveness of the corresponding defences for the attacks. The experiment results show that the proposed mechanisms can successfully defend against these attacks, and the energy consumption of these defence methods is very low.
    Keywords: wireless sensor networks; time synchronisation; security; IEEE802.15.4e.

  • Access-driven cache attack resistant and fast AES implementation   Order a copy of this article
    by Yadong Wan, Xinqiang Luo, Yue Qi, Jie He, Qin Wang 
    Abstract: The traditional Advanced Encryption Standard (AES) implementations based on four lookup tables (4-T) of 1KB size, have high encryption performance, but face access-driven cache attack at the same time. In this paper, we present an AES implementation based on one lookup table of 512B with optimised structure, named 1-T, to improve the access-driven cache attack resistant ability. Furthermore, we optimise the implementation of round function of 1-T to eliminate the speed influence from the shrunken lookup table. The experiment result shows that the attack resistant ability of 1-T is much higher than 4-Ts under the same cache setting, and that the encryption time of 1-T is increased by 43.5% and 106.3% compared with 4-Ts on the ARM and the x86 platform, respectively, but the storage overhead is only 28% of 4-Ts.
    Keywords: AES encryption; look-up table; access-driven cache attack; WSN

  • A new construction of fuzzy operator-attribute-based signcryption on VCC   Order a copy of this article
    by Wenbo Zhang, Bao Zhenshan, Yang Pengfei, Duan Lijuan, Li Juan 
    Abstract: Recently, Vehicular Computer Clouds (VCC) have assumed an important role in Intelligent Transportation System (ITS). VCC meet lots of security challenges and it so is important to build secure VCC access. In this paper, a Fuzzy Operator-Attribute-Based Signcryption (FOABS) is presented, which is a novel security mechanism that makes relations between the vehicle operators right and these operations. FOABS leverages fuzzy attribute-based encryption to enable data encryption, access control, and signature for vehicular control, and signature for vehicular control information in VCC. FOABS, which combines digital signatures and encryption, provides confidentiality, authenticity, undeniability, and collusion resistance. Through the prototype system, we analyse its security level.
    Keywords: operator-attribute-based signcryption; vehicular computer clouds; vehicular networks; access control.

Special Issue on: 3PGCIC 2014 The Challenges of Pervasive Computing Security and Intelligence

  • Static compliance checking beyond separation of duty constraints   Order a copy of this article
    by Yang Bo, Chunhe Xia, Yang Luo, Qing Tang 
    Abstract: Compliance requirements, such as separation of duty and binding of duty, have to be satisfied in many application domains. Existing compliance checking frameworks either have limited expressiveness or rely on model checking, which has a small applicable range and low efficiency. To overcome these limitations, we improve high level expression separation of duty algebra to (1) describe both SoD and BoD constraints to make it more expressive; (2) to describe a user-task relationship to perform compliance checking. In order to make the improved high level policy act on the concrete process, we (1) construct mapping rules to translate the improved high level policies to low level constraints described in description logic; (2) propose a reasoning framework to check for business process compliance. We report on the applicability of our approach via a case study.
    Keywords: business process compliance; high level policy; low level constraint; description logic; framework

  • An algorithm of video network transmission based on unbalanced multiple description coding   Order a copy of this article
    by ShanGuo Lv, YiQin Cao 
    Abstract: The drop-rate and net delay during video network transmission are two important factors in ensuring video network transmission quality. The purpose of network congestion control is to reduce the bad quality impact of video network transmission caused by net delay and the drop-rate. This paper proposes an algorithm of video network transmission based on unbalanced multiple description coding, which is capable of quickly recovering from packet losses and ensuring continuous playback, and furthermore is adaptive to both multiple path and single path transmission. A Markov model was employed to predict the state of network congestion based on available bandwidth detection, and the video transmission path was changed on the basis of the prediction. Experiments show that, compared with the RED algorithm, the algorithm is much more effective to estimate network congestion, reduce video packet loss-rate and net delay, thus the video network transmission quality can be ensured more effectively.
    Keywords: unbalanced multiple description coding ;bandwidth detection ;Markov model

  • Study on the local path planning for intelligent vehicles based on an improved VFH method   Order a copy of this article
    by Yingwei Yan, Yu Du, Wenan Zhou 
    Abstract: A local path planning method has been proposed and implemented for intelligent vehicles, the vector field histogram sharp (VFH#). In this study, an intelligent vehicle was made to manoeuvre through obstacles by the VFH# method. This local path planning method is the result of an improvement on a method called VFH (Vector Field Histogram). The VFH method is sensitive to the threshold value for determining candidate sectors. It is difficult for an intelligent vehicle to travel through narrow corridors by the VFH method. The VFH# method enlarges obstacles to avoid collisions. It also designs a new means of acquiring the magnitude of the obstacle vector to eliminate sensitivity. In each sector, it chooses the largest magnitude as the resistance value among obstacle vectors. The method is applied to an electric vehicle to verify the performance, and it achieves an excellent result.
    Keywords: local path planning; vector field histogram sharp; intelligent vehicle

Special Issue on: RFID Applications in the Internet of Things

  • A modified Q-learning algorithm to solve cognitive radio jamming attack   Order a copy of this article
    by Feten Slimeni, Bart Scheers, Zied Chtourou, Vincent Le Nir, Rabah Attia 
    Abstract: Since the jamming attack is one of the most severe threats in cognitive radio networks, we study how Q-learning can be used to pro-actively avoid jammed channels. However, Q-learning needs a long training period to learn the behaviour of the jammer. We take advantage of wideband spectrum sensing to speed up the learning process, and we use the already learned information to minimise the number of collisions with the jammer. The learned anti-jamming strategy depends on the elected reward strategy, which reflects the preferences of the cognitive radio. We start with a reward strategy based on the avoidance of the jammed channels, then we propose an amelioration to minimise the amount of frequency switching. The effectiveness of our proposal is evaluated in the presence of different jamming strategies and compared with the original Q-learning algorithm. We compare also the anti-jamming strategies related to the two proposed reward strategies.
    Keywords: cognitive radio, jamming, Markov decision process, Q-learning

  • RFID IoT-enabled warehouse for safety management using product class based storage and potential fields methods   Order a copy of this article
    by Sourour Trab, Eddy Bajic, Ahmed Zouinkhi, Mohamed Naceur Abdelkrim, Hassen Chekir 
    Abstract: Security and risk management in warehouses and logistics is a key factor to achieve a sustainable and safe supply chain. The paper aims at proposing RFID-IoT-enabled warehouse management focused on safety assurance for goods and people leveraging product Class Based Storage (pCBS), communicating object, RFID and IoT components. Security issues between products, storage locations, transportation equipment, environment and people are handled with the use of potential fields methods associated with smart product management in RFID-IoT warehouse architecture. A dynamic calculation of suitable storage locations is proposed founded on negotiation mechanisms between products and shelves, and their availability and compatibility constraints according to the pCBS method. A safe and secure product storage path discovery method is presented using attractive/repulsive potential fields for path minimisation while maximizing security level along the way. A multi-agent based simulation with NetLogo demonstrates the effectiveness of the proposal allowing to achieve safety warehouse management by using smart product reactivity against critical risks.
    Keywords: product class based storage, potential fields methods, communicating object, IoT, RFID, negotiation mechanisms, simulation, NetLogo.

Special Issue on: Advanced Mobile Cloud Computing and Internet of Things Systems and Networking

  • GARCH and ANN based DDoS detection and filtering in cloud computing environment   Order a copy of this article
    by Brij Gupta 
    Abstract: Nowadays, Distributed Denial-of-Service (DDoS) attack is one of the major security threats in cloud computing environments as it compromises the availability of the services and risks everything, including financial loss, reputation and losing faith of the customers. In this paper, we present our proposed technique which can detect and filter various DDoS attacks in cloud environments. It uses a nonlinear time series (GARCH) model to correctly predict the traffic state as it is able to capture long-range dependence (LRD) and long-tail distribution, which is the property of general network traffic. Moreover, chaos theory is used for the DDoS attack detection. Filtering is done with the help of a back-propagation artificial neural network (ANN) on the traffic that exceeds the certain limit specified by some threshold. Experimental results show the supremacy of the proposed approach over other approaches.
    Keywords: DDoS, cloud computing, nonlinear time series model, GARCH model, artificial neural network

  • An approach to transform Internet of Things data into knowledge   Order a copy of this article
    by Ivaylo Atanasov, Anastas Nokolov, Evelina Pencheva 
    Abstract: The concept of Internet of Things (IoT) will play an essential role in future applications aimed at optimisation of energy consumption. Interoperability of IoT applications can be achieved by usage of data models that explicitly determine the structure of information exchanged between applications. This paper presents a layered approach to modelling semantic information for IoT applications aimed at improving energy efficiency. Physical systems are is modelled as things that can be observed and actuated. The observations and actuations are context-aware and may be used to control processes in the physical systems. The purposive usage of observations and actuations is defined as a service model exposing generic capabilities that can be shared across different applications. The service model is described by RESTful Web Services for power control. The potential of Web Services for home appliance energy efficiency is estimated.
    Keywords: Internet of Things, smart home, power control, ontology, semantic models, RESTful Web Services

  • A verifiable framework for smart sensory systems   Order a copy of this article
    by Mohammed Al Zamil 
    Abstract: Reliability of smart systems, which are implemented using wireless sensor networks (WSNs), is an emerging quality requirement. The backbone infrastructure requires network controllers and service programs to share some computing resources, forcing them to interleave concurrently to perform their designated tasks. Such weaving affects the overall reliability, modularity, and scalability of these systems, especially in critical domains. Therefore, separating the implementation of network controllers from the implementation of service programs in a modular design will facilitate enhancing their quality and safety properties. In this paper, a software design pattern is proposed for the purpose of modularising the design of WSN software components. The proposed design pattern handles the cross-cutting concerns in which interleaving problems are automatically detected at design time. Furthermore, the proposed framework allows for abstracting complex systems into finite-state-automata (FSA) to depict their behavioral transitions. Such abstraction allows for checking the reliability aspects that result from the concurrent interactions among the systems components. The framework has been applied on two case studies: smart irrigation and smart grid models. In both experiments, the proposed technique was able to detect the synchronisation errors, which frequently appear in such systems. Furthermore, additional experiments on the effect of the proposed design on the WSN power consumption have been performed. The results showed that the proposed modular design minimises the communicating messages and, therefore, the required level of energy.
    Keywords: wireless sensor networks; design for verification; software defined networking; power consumption; data mining

  • A smart mobile cloud environment for modelling and simulation of mobile cloud applications   Order a copy of this article
    by Manel Gherari, Abdelkrim Amirat, Ridda Laouar, Mourad Oussalah 
    Abstract: Mobile Cloud Computing (MCC) has been introduced as an optimal solution to the constrained mobile devices. MCC takes mobile devices to a wholly new level where the latter rely on the cloud to store and process data. Since mobile cloud applications encompass more complicated and rich architectural features, they are considered as the next generation of mobile applications. Thereby new challenges arise in their development phase, such as addressing issues of communication with the hybrid cloud, dynamic configuration, exploiting the concept of mobility and contextual information. Being different from traditional applications, this new kind of application requires new methods, techniques and tools of development, modelling and simulation. Addressing this lack in MCC, we propose in this paper a context-aware based framework that allows: a) the description of mobile cloud applications architecture with the Mobile Cloud Architecture Description Language (MC-ADL); b) the simulation of mobile cloud application behaviour in a simulated cloud environment using mobile cloud simulation toolkit (MC-SIM); c) the provision of a context-aware middleware, Smart Cloud Gate (SCG), to ensure contextual configuration of the mobile cloud application at runtime level and contextual evolution of its architecture.
    Keywords: mobile cloud computing; mobile cloud computing modeling; mobile cloud computing simulation; model transformation; context awareness; mobile cloud middleware.

  • A framework for computational offloading to extend the energy of mobile devices in mobile cloud computing   Order a copy of this article
    by P Thanapal, M A Saleem Durai 
    Abstract: In this paper, we devise a novel offloading policy for energy-efficient mobile cloud computing. Limitations, such as poor processing ability and limited battery life, make it difficult for mobile devices to process complex computational tasks. The mobile devices in traditional local processing find it difficult to execute high-bandwidth-consuming videos, and solve this problem by offloading complex executions of the application onto cloud computing to minimise the processing requirements and energy consumption of the mobile device, thereby overcoming the limitations of poor processing ability and limited battery life. The energy-efficient framework focuses on Mobile Cloud Computing (MCC), which employs computational offloading for computationally intensive mobile applications on mobile devices. An input device, namely a VNC (Virtual Network Computing) client, is installed on the local mobile device and connected to the VNC server, which is installed in the cloud. Energy consumption of the selected application is reduced up to 67.19% by computational offloading compared with traditional methods. The results were observed to be encouraging.
    Keywords: cloud computing, energy efficiency, offloading, green computing, mobile cloud computing, mobile device, computational offloading, virtual machine, virtual network computing, Amazon elastic compute cloud

  • Cloudlet-based ad-hoc mobile cloud computing: design and evaluation   Order a copy of this article
    by Mohammad Al-Rousana, Elham Alshara, Yaser Jararweh, Mohammad Al-Shayeji 
    Abstract: In this paper, a cloudlet-based approach for a new ad-hoc model for mobile-based cloud computing is proposed. The performance of the model is evaluated using Destination-Sequenced Distance-Vector (DSDV) for routing protocol and Random Way Point mechanism (RWP) for mobility fashion. The important parameters used to evaluate the model are end-to-end (e2e) packet delay, system scalability and mobility management. The performance of the model has been studied using various workload sizes that are offloaded to cloudlets and for different node speeds. The variation of hand-off delay, as well as workload size, has a significant impact on the e2e delay results. Even with the maximum hand-off delay, passing various workloads through multiple cloudlets it still lower than using an enterprise cloud unless offloading small workload size.
    Keywords: mobile cloud computing, cloudlet, ad-hoc model, performance evaluation

Special Issue on: PCC 2014 Frontiers in Pervasive Computing

  • Energy-aware list-based scheduling for parallel applications in cloud   Order a copy of this article
    by Yongxing Liu, Kenli Li, Zhuo Tang, Keqin Li 
    Abstract: As the growth of energy consumption has been explosive in current data centres and cloud systems, it has drawn greater attention in academia, industry and government. Task scheduling is core to systems, it has become an important method to reduce energy dissipation. This paper proposes an Energy Aware List-based Scheduling algorithm called EALS for parallel applications in the context of Service Level Agreements (SLA) on cloud data centres. First, the EALS algorithm comprehensively considers the high power processors to minimise the number of high power processors used. Then, the algorithm tries to migrate some tasks from a high power processor to a low power processor for energy saving. Finally, the EALS algorithm takes a more efficient way to assign the time slots among tasks based on the dynamic voltage scaling (DVS) technique. To demonstrate the effectiveness of the EALS algorithm, randomly generated graphs and several real-world applications are tested in our experiments. The experimental results show that the EALS algorithm can save up to 43.96% energy consumption for various parallel applications as well as balance the scheduling performance.
    Keywords: cloud data centre; directed acyclic graph; dynamic voltage scaling; energy-aware scheduling; service level agreement.

  • User similarity based gender-aware travel location recommendation by mining geotagged photos   Order a copy of this article
    by Zhenxing Xu, Ling Chen, Haodong Guo, Mingqi Lv, Gencai Chen 
    Abstract: The popularity of camera phones and photo-sharing websites, e.g. Flickr and Panoramio, has led to huge volumes of community-contributed geotagged photos, which could be regarded as digital footprints of photo takers. Thus, mining geotagged photos for travel recommendation has become a hot topic. However, most existing work recommends travel locations based on the knowledge mined from photo logs (e.g. time, location), and largely ignores the knowledge implied in the photo contents. In this paper, we propose a geotagged photos mining-based personalised gender-aware travel location recommendation approach, which considers both photo logs and photo contents. Firstly, it uses an entropy-based mobility measure to classify geotagged photos into tour photos or non-tour photos. Secondly, it conducts gender recognition based on face detection from tour photos. Thirdly, it builds the gender-aware profile of travel locations and users. Finally, it recommends personalised travel locations considering both user gender and similarity. Our approach is evaluated on a dataset, which contains geotagged photos taken in eleven cities of China. Experimental results show that our approach has the potential to improve the performance of travel location recommendation.
    Keywords: geotagged photos; gender recognition; travel location recommendation

  • An abstraction layer enabling pervasive hardware-reconfigurable systems   Order a copy of this article
    by Alessandro Cilardo, Nicola Mazzocca, Paolo Prinetto 
    Abstract: Field-programmable gate array technologies are creating a new range of challenges for pervasive and ubiquitous systems. Revisiting and extending approaches borrowed from the purely software domain is a fundamental opportunity in this scenario. In particular, this paper addresses code mobility, a well-established approach used to dynamically adapt a distributed system based on the actual application needs, and extends it to a deep code mobility concept, allowing "logical" hardware components to be migrated across a pervasive infrastructure. The work presents the architecture and the prototype implementation of a reconfigurable computing framework providing full support to deep code mobility through an abstraction layer which exposes a portable view of the underlying reconfigurable hardware. The paper then thoroughly discusses two application scenarios, hardware-accelerated distributed data mining and autonomous online testing, confirming the impact of deep code mobility in real-world pervasive computing contexts.
    Keywords: pervasive computing; ubiquitous systems; code mobility; adaptive systems; reconfigurable computing; field programmable gate array

  • Scheduling deadline-constrained scientific workflow using chemical reaction optimisation algorithm in clouds   Order a copy of this article
    by Chaokun Yan, Huimin Luo, Zhigang Hu 
    Abstract: The advent of cloud computing as a new model of service provisioning in distributed systems encourages researchers to investigate its benefits and drawbacks on executing scientific applications such as workflows. One of the most challenging problems in clouds is workflow scheduling, i.e., the problem of satisfying the QoS requirements of the users as well as minimising the cost of workflow execution. In this paper, a novel meta-heuristic method, called chemical reaction optimisation (CRO), is developed to solve deadline-constrained workflow scheduling, which tries to minimise the cost of workflow execution while meeting a user-defined deadline. A set of appropriate parameter can be obtained based on orthogonal experimental designs (OED) and factor analysis. Experiments are done in two real workflow applications, and the results demonstrate the effectiveness of the proposed algorithm.
    Keywords: cloud; SaaS; deadline; scientific workflow; chemical reaction optimisation

Special Issue on: ICA3PP 2015 and PRDC 2015 Dependability in Parallel and Distributed Computing

  • A language-based intrusion detection approach for automotive embedded networks   Order a copy of this article
    by Studnia Ivan, Eric Alata, Vincent Nicomette, Mohamed Kaaniche, Youssef Laarouchi 
    Abstract: The increase in connectivity and complexity of modern automotive networks presents new opportunities for potential hackers trying to take over a vehicle. To protect the automotive networks from such attacks, security mechanisms, such as firewalls or secure authentication protocols, may be included. However, should an attacker succeed in bypassing such measures and gain access to the internal network, these security mechanisms become unable to report about the attacks causing such a breach, occurring from the internal network. To complement these preventive security mechanisms, we present a non-intrusive network-based intrusion detection approach fit for vehicular networks, such as the widely used CAN. Leveraging the high predictability of embedded automotive systems, we use language theory to elaborate a set of attack signatures derived from behavioural models of the automotive calculators in order to detect a malicious sequence of messages transiting through the internal network.
    Keywords: automotive networks; security; intrusion detection; CAN; finite state automata; regular languages

  • Area Coverage Estimation Model for Directional Sensor Networks   Order a copy of this article
    by Zhimin Liu, Weijia Jia, Guojun Wang 
    Abstract: Recently, directional sensor networks (DSNs) have received a great deal of attention owing to their wide range of applications in different fields. A directional sensor has a smaller angle of sensing range than an omni-directional sensor. Coverage is one of the fundamental problems of directional sensor networks at present, which reflects how well the environment is monitored. In this paper, we propose a coverage estimation model to estimate the coverage problem with boundary effect. In order to guide initial deployment of DSNs and better meet requirements with certain initial coverage probability effectively, a novel probability-based area coverage estimation model with boundary effect, named PCPMB, is proposed. Simulation results show that our proposed model outperforms the previous proposed model without boundary effect.
    Keywords: directional sensor networks; area coverage; coverage estimation; node estimation.

  • An analytic evaluation on soft error immunity enhancement due to temporal triplication   Order a copy of this article
    by Ryutaro Doi, Masanori Hashimoto, Takao Onoye 
    Abstract: The chip-level soft error rate is increasing, owing to device miniaturisation and larger scale integration. Soft errors are one of the major factors that degrade the reliability of integrated circuits, and soft error aware design is demanded for applications that cannot allow any failures. As one of the soft error countermeasures, spatial redundancy has been widely studied and adopted in real products because of its small speed overhead and easiness of implementation. On the other hand, temporal redundancy, which is another well-known technique, is rarely adopted in practical applications and its usefulness has not been comparatively evaluated. This paper analytically evaluates the soft error immunity enhancement thanks to temporal triplication. The evaluation result shows that the failure rate reduction of the temporal triplication is comparable with that of the spatial triplication in the supposed pipeline hardware and computation model.
    Keywords: reliability; soft error; redundancy; temporal triplication; spatial triplication.

Special Issue on: Security for Embedded and Related Systems

  • Identification and addressing of the internet of things based on distributed ID   Order a copy of this article
    by Rui Ma, Yue Liu, Ke Ma 
    Abstract: It is a key issue that identification and addressing the entity which access the Internet through the wireless network with various short distance transmission protocols. To solve the problem, combining with the existing identification and addressing technology of the Internet and the IOT, this paper proposes a method based on distributed ID. This method can be divided into two stages. It first designs the structure of distributed ID. Using the distributed address allocation algorithm, it implements the automatic allocation of the distributed ID as well as the distributed ID resolution among the global IOT. After that, an addressing scheme is designed to meet demands of the IOT addressing. It first defines the structure of addressing and then implements the routing addressing algorithm which combines the cluster-tree algorithm with the ad-hoc on-demand distance vector routing algorithm. This scheme could improve the routing efficiency as well as achieve lower cost, lower energy consumption and higher reliability of the addressing. By the simulation on NS-2 platform, the experimental results highlight the feasibility and effectiveness of the proposed method from three aspects: the correctness of identification allocation, the effectiveness of addressing scheme, and the stability of data transmission.
    Keywords: internet of things; identification; addressing; AODV; cluster-tree

  • Constant-size ring signature scheme using multilinear maps   Order a copy of this article
    by Xiangsong Zhang, Zhenhua Liu, Fenghe Wang 
    Abstract: Ring signature is a group-oriented digital signature with anonymity. Most existing ring signature schemes use bilinear pairings, are provably secure in the random oracles, or are linear signature size to the number of ring member. In this paper, we use multilinear maps, which have been widely used to construct many novel cryptographic primitives recently, to present a ring signature scheme with constant signature size. The proposed scheme is proven to be anonymous against full key exposure and unforgeable against chosen-subring attacks based on the multilinear computational Diffie-Hellman assumption in the standard model. Furthermore, our scheme has the advantage of tighter security reduction by using an optimal security reduction technique.
    Keywords: ring signature; multilinear maps; security reduction; provable security; standard model.

  • Zero-knowledge identification scheme with companion matrices of primitive polynomials   Order a copy of this article
    by Huawei Huang, Lunzhi Deng, Yunyun Qu, Chunhua Li 
    Abstract: This paper proposes the matrix power problem, that is, to find x given C^xD^x, where C and D are the companion matrices of primitive polynomials over finite field. A new zero-knowledge identification scheme based on matrix power problem is proposed. It is perfect zero-knowledge for honest verifiers. Owing to its simplicity, low-memory and low-computation costs, the proposed scheme is suitable for using in computationally limited devices for identification, such as smart cards.
    Keywords: finite field; primitive polynomials; companion matrix; discrete logarithm problem; identification scheme.

  • Identification of cascading dynamic critical nodes in complex networks   Order a copy of this article
    by Duan Dong-Li 
    Abstract: Catastrophic events occur frequently on the internet, power grids as well as other infrastructure systems, which can be considered, to some extent, to be triggered by minor events. To study the dynamic behaviour of these systems, we generally should simplify them as networks. The reason lies in that the network can be seen as the skeleton embedded in the internet system, power grid, transportation and traffic system, as well as other infrastructure systems. We should pay more attention to these backbone networks so as to explore the dynamic behaviour and mechanisms of the embedded systems more deeply and broadly. One of the major problems in the field of networks is how to identify the critical nodes. In this paper, we explore the identification method of cascading dynamic critical nodes in complex networks. By the average load oscillation extent of the affected nodes caused by attacking one node, we define the importance indicator of the attacked node with a cascading failure model based on a load preferential sharing rule. The indicator has two characteristics: one is that the failure consequence of the considered node can be clearly pointed out by its value. If I(i) ≥ 1, the node I will trigger the next round overload. If I(i) < 1=ki , the node i will be a single failure. If 1=ki ≤ I(i) < 1, the outcome will not be determined, namely the failure of i may trigger the overload of its neighbour node or may not. The other is that the evolution mechanism of node importance can be analysed with the factors of load redistribution mechanism, node capacity, and structural characteristics of the network. For example, we can see that the value of i determines the distribution of the node importance: in the case i = 1 we have I(i) ∼ k0 i , namely the node importance is independent of the nodes degree. If  ̸= 1 we have I(i) ∼ k-1 i , the node importance scales with the node degree and P(I) is driven by P(k). The experiments demonstrate the effectiveness and feasibility of the indicators and its algorithm, with which we also analyse the node importance evolution mechanism in depth.
    Keywords: complex networks; node importance; cascading failure; load redistribution rule; overload mechanism; scale-free networks; ER networks; power grid.

Special Issue on: Advances in Biometrics and Their Security in Cloud Computing

  • Three-dimensional face reconstruction based on average face model and photometric stereo   Order a copy of this article
    by Yujuan Sun, Xiaofeng Zhang, Yongqing Lei 
    Abstract: Three-dimensional reconstruction of the classical photometric stereo is based on the reflected light of the object. The reconstructed results have good high-frequency characteristics. However, owing to the uneven distribution of the reflected light, the low-frequency characteristics of the reconstructed results are poor. In this paper, the average face model has been used to improve the low-frequency characteristics of the classical photometric stereo. By fusing the low frequency of the average face model and the high-frequency of photometric stereo, the accuracy of the three-dimensional face shape has been largely improved. The face images in YaleB database have been used to verify our algorithm. Experimental results of the proposed approach are more effective and accurate than those of classical photometric stereo.
    Keywords: 3D reconstruction; human face; photometric stereo

  • A novel Slant transform-based image feature extraction algorithm   Order a copy of this article
    by Jinglong Zuo, Delong Cui, Qirui Li 
    Abstract: In order to improve the efficiency and simplify the steps of generating an image hashing, a secure and robust image hashing algorithm based on Slant transform is proposed in this paper. By employing the coefficients of Slant transform, a robust hashing sequence is obtained by preprocessing, feature extracting and post processing. The security of the proposed algorithm is totally dependent on the user-keys which are saved as secret keys. Several benchmark images are used to show the feasibility of the image-hashing algorithm. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image, such as JPEG compression, mid-filtering, and rotation. Therefore, the scheme proposed in this paper is suitable for image authentication, content-based image retrieval, and digital watermarking, etc.
    Keywords: image hashing; Slant transform; normalised Hamming distance; encryption keys

  • Defects of wheel hubs detection and recognition based on trend peak algorithm   Order a copy of this article
    by Wei Li, Kangshun Li, Ying Huang 
    Abstract: In industrial applications, automatic detection of automotive wheel hub defects has important significance to improve the quality and efficiency of automotive wheel production, and vehicle safety. In order to improve accuracy of detection and recognition of automotive wheel hub defect images, an improved peak location algorithm, the trend peak algorithm, is proposed to extract the region of wheel hub defects, combined with BP neural network to classify and recognise the defects. Firstly, initial defect positions are extracted using peak locations of vertical and horizontal directions. Then mathematical morphology is used to remove pseudo defects, and the exact locations of the defects are obtained. Finally, the wheel hub defect features are classified to reach the target of defect recognition by BP neural network. In actual industrial conditions, the algorithm is found to give good recognition results and reach real-time detection request in low contrast, high noise, uneven illumination, and complex structure of the products, by experiments of X-ray images of four common defects of actual wheel hubs.
    Keywords: wheel hubs of automobiles; X-ray image; trend peak algorithm; defect detection, defect recognition.

  • A finger vein recognition algorithm based on deep learning   Order a copy of this article
    by Cheng Chen, Zhendong Wu, Jianwu Zhang, Ping Li, Freeha Azmat 
    Abstract: Deep learning has recently achieved impressive performance in the area of biometric recognition. The technology of finger vein recognition possesses better anti-forgery performance and identification stability in collecting and certificating information of human bodies. The traditional finger vein recognition method is mainly based on template matching or whole feature recognition, and suffers from light instability of the acquisition equipment which leads to low robustness. In this paper, we adapt a finger vein recognition algorithm using Feature Block Fusion and Deep Belief Network (FBF-DBN) and a convolutional neural network (CNN). We combine these two network systems to judge the performance of our system. Meanwhile, we improve the deep network input by using feature points set in vein images, effectively reducing the time in learning and detection, meeting the practical needs of biometric recognition specifically applied to embedded equipment. The experiment results showed that the FBF-DBN and CNN algorithm present better recognition performance and faster speed.
    Keywords: feature block fusion; deep belief network; convolution neural network; finger vein recognition

  • Fusing multiple features and spatial information for image classification via codebook ensemble   Order a copy of this article
    by Huilan Luo, Chengtao Wan, Minjie Guo 
    Abstract: The construction of a codebook is an important step which is usually done by cluster analysis. However, clustering is a process that retains regions of high density in a distribution, and it follows that the resulting codebook need not have discriminate properties. This paper presents a discriminative spatial codebook ensemble learning approach for image classification with three key innovations. (1) Images are first divided into sub-regions according to a spatial pyramid, and then initial big member spatial codebooks are constructed by grouping features of sub-regions into a number of clusters, one member spatial codebook for one sub-region. (2) The discriminative member spatial codebook is formed by selecting the visual words with higher probability of occurring in the images. Then the features of each sub-region are coded by LLC based on its corresponding member codebook. (3) Combining SIFT and KDES-G features to describe images is also proposed by generating a joint vector as a new feature vector. The experimental results on the Caltech 101 and 15 Scenes datasets have shown that the proposed method has better performance and robustness compared with some state-of-the-art works.
    Keywords: image classification; feature fusion; codebook ensemble.

  • A novel WDM-PON based on quantum key distribution FPGA controller   Order a copy of this article
    by Yunlu Wang, Hao Wen, Zhihua Jian, Shuhuai LI 
    Abstract: To improve the potential security threats of WDM-PON access network, a novel WDM-PON based on quantum key distribution FPGA controller of passive decoy state modified model is presented here. QKD FPGA is responsible for 1.25 Gbps upstream PRBS source, clock regeneration, phase modulation control, key sifting, privacy amplification, and upstream time-divided-multiple-access control on quantum channels. An 8-user network experiment shows that over 20 km fibre, the mean secure exchange key rate can reach up to 500 bps in total, with the acceptable quantum bit error rate below the safe limit and little impact on classical channels. This scheme can provide a promising way for the coexistence between quantum key distribution and classical data service.
    Keywords: quantum cryptography; WDM PON; quantum key distribution; quantum communication; optical fibre communication; decoy state

  • A near-field magnet peak values detecting method to locate short-circuit points on PCB   Order a copy of this article
    by Shuqiang Huang, Jielin Zeng, Hongchun Zhou, Zhusong Liu, Yuyu Zhou 
    Abstract: The existing print circuit board (PCB) short circuit fault detecting schemes can only determine the existence of shorts rather than the precise location of the circuit. To solve this problem, the paper determines a short-circuit location detecting scheme based on the near-field magnetic specific point. First, the existence of the shorted wires is detected by a short circuit detecting algorithm. Second, the short-circuit networks are excited by a high voltage. Third, the peak values of the magnetic near-field excited by the voltage are detected by the sensors arranged above the circuit board and analysed. This scheme locates the precise position of the short-circuit point on the board. The simulation results show that the technique is operational and can effectively locate the short-circuit point position.
    Keywords: PCB, short circuit, near-field magnet detecting, impendence mismatch, magnetic sensor

  • An improved parallel K-means algorithm based on MapReduce   Order a copy of this article
    by Dongbo Zhang, Jianmin Xu, Yanfang Shou 
    Abstract: The K-means algorithm is one of the most popular clustering algorithms. However, it is sensitive to initialised partitions and circular datasets. To address this problem, this paper introduces a CK-means clustering algorithm based on the K-means algorithm and the Canopy algorithm, which uses the MapReduce programming model of the Hadoop platform. The experimental results prove that the CK-means algorithm has strong advantages for processing large datasets. The theoretical analysis shows that the CK-means algorithm and the traditional algorithm are of the same order of magnitude. The experimental results on artificial data show that the improved algorithm is better than the traditional algorithm in terms of acceleration ratio, accuracy and expansion rate. An experiment on real data is performed to obtain appropriate parameters.
    Keywords: cloud computing; MapReduce model; k-means clusters; Canopy algorithm; big data

  • Prosodic features based speaker verification using speaker-specific-text for short utterances   Order a copy of this article
    by Zhang Jianwu, He Jianchao, Wu Zhendong, Freeha Azmat, Li Ping 
    Abstract: Over the past several years, Gaussian mixture models have been a dominant approach to modelling in the text-independent speaker recognition field. But the recognition accuracy of these models declines when utterances length becomes short. At present, Mel-frequency Cepstral coefficients are generally used to characterise the properties of the vocal tract and are widely applied in speech recognition. In addition, prosodic features, such as pitch and format, are generally considered to describe the glottal characteristics. However, the efficiency of those approaches remains unsatisfactory. In text-dependent short utterance speaker verification systems, prosodic features can assist to improve the recognition result theoretically. In order to optimise the performance of speaker verification systems under the framework of adapted GMM-UBM, we adopt a variant speaker verification system based on prosodic features, in which a dual judgement mechanism is used in order to integrate vocal tract features with prosodic features. Experimental results showed that the new speech recognition system led a better consequence.
    Keywords: speaker verification; text dependent; prosodic features; dual judgement mechanism

Special Issue on: Advances in Cyber Security, Analytics and Human Factors in IT

  • An intelligent paradigm for denoising motion artifacts in ECG processing: smart filters   Order a copy of this article
    by Maheswari Arumugam, Arun Kumar Arumugam Sangaiah 
    Abstract: A well recorded ECG contains complete information about the various heart diseases. The detection of cardiac diseases involves several stages, such as ECG signal pre-processing, feature extraction, feature classification and finally the identification of the cardiac disease from the detected abnormality. This paper concentrates on pre-processing of the ECG signal, which is the fundamental stage in the analysis of cardiac diseases. The identification of the various kinds of heart disease depends on accurate analysis of ECG signals. The analysis of a heart signal will be precise and accurate only if it is completely free from noise signals. A minute change in ECG due to noise signals changes the characteristics of ECG, which results in a wrong diagnosis of the heart disease. The main focus of this paper is on developing a novel smart filter design and implementing the proposed design for filtering the main noise signals that distort the original ECG signal. The main noise signals are identified as power line interference, baseline wander and electromyography. In this paper the proposed filter design is compared in terms of signal to noise ratio and power spectral density. Further, the comparison result indicates that the proposed filter design has a good response characteristic for noise filtration. The eradication of these noise signals helps us to achieve correct identification of heart disease and makes the life of physicians easier.
    Keywords: preprocessing; electrocardiogram; smart filter; baseline wander; power line interference; electromyography; signal to noise ratio

  • An efficient ternary tree-based TGDH protocol for dynamic secure group data sharing in cloud computing   Order a copy of this article
    by Vaishali Thakare, John Singh 
    Abstract: The current cloud computing system consists of a large amount of sensitive data shared by cloud users. This sensitive data sharing is done in secure groups. Here, privacy and security of the group sharing data have become the two major issues, whereas secure and reliable group communication is a fertile research area that has gained a wide popularity in group-oriented and collaborative applications. Designing a dynamic, secure and efficient group-sharing framework is one of the important challenges in cloud computing. Because the cloud provider is a semi-trusted third party, traditional security frameworks cannot be used in group sharing. In this paper a TGDH ternary tree based secure group-sharing framework is proposed. TGDH with a ternary tree-based approach is more efficient than the binary tree approach in terms of strength of members in a subgroup, and the height of the binary tree increases when the number of members in a group increases, where the height of the tree is the number of iterations required to compute the group shared key. Similarly, computation and communication cost also increases when the number of members of a group increases proportionally. Furthermore, to show the strength of our proposed framework, the statistical comparison with existing TGDH protocol is shown. Finally, the extensive simulation results with CloudSim tool are shown to demonstrate the resource use by each member, VM allocation, cloudlets allocation and execution time of proposed construction.
    Keywords: cloud computing; TGDH protocol; group data sharing; security; ternary tree.

  • Privacy-preserving secret key extraction protocol for multi-authority attribute-based encryption techniques in cloud computing   Order a copy of this article
    by P.G. Shynu, John Singh K 
    Abstract: In the existing privacy-preserving Multi-Authority Attribute-based Encryption (MA-ABE) techniques, the users receive their secret keys from multiple authorities, where each authority maintains a different set of user attributes with major control established over a central authority, who manages all the attribute-related activities (causes collision attack). In such a type of scheme, the secret key is derived from user-sensitive attributes. But this enables multiple authorities to collect and analyse the user attributes with the intent to recognise a users identity, and this leads to compromised key attack and insider attack. In order to solve this issue, this paper defines a Privacy Preserving Secret key Extraction protocol (PPSE), which stores user attributes in a fuzzy attribute set format over the hash index. The hash index acts as a unique identity that enables easier extraction of the secret key from outsourced user attributes and it eliminates the need for the involvement of a central authority for user attribute management processes. This work is implemented using Charm Crypto (Akinyele et al., 2013), an extensible framework for rapid prototyping system. The experimental results show that our proposed scheme provides higher levels of user access provision with improved security and privacy properties in comparison with existing MA-ABE techniques.
    Keywords: cloud computing; multi-authority attribute-based encryption; privacy-preserving secret key extraction protocol; fuzzy attribute set.

  • Automated identification of callbacks in Android framework using machine learning techniques   Order a copy of this article
    by Xiupeng Chen, Rongzeng Mu, Yuepeng Yan 
    Abstract: The number of malicious Android applications has grown explosively, leaking massive privacy sensitive information. Nevertheless, the existing static code analysis tools relying on imprecise callbacks list will miss a high number of leaks, which is demonstrated in this paper. This paper presents a machine learning approach to identifying callbacks automatically in the Android framework. As long as there is a training set of hand-annotated callbacks, the proposed approach can detect all of them in the entire framework. A series of experiments are conducted to identify 20,391 callbacks on Android 4.2. This proposed approach, verified by a ten-fold cross validation, is effective and efficient in terms of precision and recall, with an average of more than 91%. The evaluation results show that many of newly discovered callbacks are indeed used, which furthermore confirms that the approach is suitable for all Android framework versions.
    Keywords: callbacks identification; machine learning; support vector machine; cross validation; static analysis; malware; privacy; Android framework; mobile application security.

  • Recovering multiple versions of YAFFS2 files based on hash and timestamps   Order a copy of this article
    by Yameng Li, Jingsha He, Na Huang, Gongzheng Liu 
    Abstract: With the popularity of digital devices, especially Android-based devices, digital forensic research targeted at Android-based devices has drawn increasing attention. Among the many issues in digital forensics, data recovery is one of the most important and has thus received a great deal of attention. In data recovery, deleted or updated data may contain important information about past activities of the user, making such information viable evidence as far as digital forensics is concerned. In this paper, according to special characteristics of YAFFS2, we propose a new method based on the notions of hash and timestamp to recover multiple versions of YAFFS2 files during which the relationship between timestamps and file operations are analysed. To verify the effectiveness of our proposed method, we will simulate a NAND chip under Linux and perform some experiments to show that the proposed method is both effective and efficient in the recovery of multiple versions of different types of YAFFS2 files as well as Android images.
    Keywords: security; digital forensics; data recovery; Android; YAFFS2; hash; timestamp.

  • A framework and a process for digital forensic analysis on smartphones with multiple data logs   Order a copy of this article
    by Elhadj Benkhelifa, Benjamin Thomas, Loai Tawalbeh, Yaser Jararweh 
    Abstract: Nowadays, mobile devices are considered an essential component of our daily lives. The rapid evolution in mobile computing has becomes a frustrating factor for law enforcement and the forensic community at large, because of the lack of industry standards, tools and training. Smartphones are becoming the most difficult to extract evidentiary data from. While many commercial forensic tools have made great strides in supporting data extraction, decoding, and analysis, some challenges remain. The smartphones not only keep us connected but also can act as a mobile office, a social tool, and an entertainment centre. The combination of functionality, processing power, and storage space makes smartphones a prime target for investigators. To our knowledge, there is no mobile forensic analysis solution that maps data from different sources including calls, geographical location, multimedia, and web logs. Based on this motivation, in this paper, we aim to propose a framework solution, which could contribute to the development of a novel and potentially market-leading mobile forensic tool.
    Keywords: mobile computing; digital analysis; side channel attacks; cryptography.

  • Token security for the internet of things   Order a copy of this article
    by Sudha Narendrakumar, Abdul Razaque, Varil Patel, Muder Almi’ani, Syed S. Rizvi, Akshat Hans 
    Abstract: The Internet of Things (IOT) is a phenomenon in which persons, things, and all other data are provided with specific identities and sending and receiving data does not require person to person or person to computer interconnection over a network. IOT has the potential to provide unlimited benefits in daily life, and the number of IOT devices is growing day by day. This scenario leads the internet world to be less secure. Since storage in each device is the main issue, cloud servers are relied upon to store the data. The data is accessed by the registered users for that particular network leading to the problem of security when many devices try to access the same network. However, the One-Time Password (OTP) method to start the session is not enough for a secured connection. The previously existing secured connection algorithms, such as OAuth, are sometimes hacked by attackers. Most of the secured connections, such as accessing a bank website, are started with token-authentication. Even though the tokens are generated only for a particular session, it is prone to be vulnerable for the guessing attacks and inviting the malicious adversaries to exploit confidential data. Most of the home devices controlled by network companies could not provide more security as promised. Nowadays starting the session with the token is considered one of the easiest and secure ways to establish a secure connection. Therefore, in this paper, we introduce the two-factor verification and authentication method involved with hashing to secure the tokens issued for the connection. The security is provided at the identity provider layer that works on the TCP/IP layer. First, the authentication and authorisation are confirmed through two-way authentication, and the token is generated by the relying party. Since the generated token has a threat of guessing or cryptanalysis attack, we worked on making it more secure by using the cryptanalytics process. The cryptanalytics process is accomplished through the addition of logical operation of the token with OTP and hashing before sending the token to the user and service provider.
    Keywords: open authentication; one time password; hash-based message authentication code; RSA; SHA relying party; pseudorandom number generator; DSA PRNG ANSI X9.7 PRNG; data encryption standard; message-digest algorithm; service provider; identity layer.

Special Issue on: ICNC-FSKD'15 Theory and Practice on Internet of Things

  • Using zero moment point preview control formulation to generate nonlinear trajectories of walking patterns on humanoid robots   Order a copy of this article
    by Yunn-Lin Hwang, Thi-Na Ta, Kun-Nan Chen 
    Abstract: This paper design a desired Zero Moment Point (ZMP) trajectory and create a Centre of Mass (CoM) trajectory based on this ZMP, in order to solve the problem of generating nonlinear trajectories of walking pattern in stability a humanoid robot. The preview control formulation which follows the planned ZMP patterns while reducing the jerk (acceleration derivation) is considered to implement this trajectory. The walking pattern for a bipedal robot is generated by using a cart-table model. After that, the hip and foot trajectories planning that make the robot walk smoothly on the different ground conditions are proposed by using the cycloid function. According to these trajectories, the position of each leg joint of humanoid robot could be determined by inverse kinematics. Then, computer simulations are performed by using RecurDyn and MATLAB softwares to validate the proposed preview control formulation for the nonlinear walking patterns generation of a Bioloid humanoid robot. Finally, an experimental analysis with the real Bioloid robot is also described in this study.
    Keywords: centre of mass; humanoid robot; zero moment point; cart-table model; preview control; CoM Jacobian.

  • An adaptive denoising method for colour images of mobile phone based on bivariate shrinkage function   Order a copy of this article
    by Xuehui Wu, Xiaobo Lu 
    Abstract: The photography function of mobile phones has become the current trend, and the image quality has become our focus. The requirements for image denoising performance of mobile phones are higher and higher. This is different from traditional image denoising because mobile phone image denoising needs faster speed, less computing space and time, and higher efficiency. Wavelet transform denoising algorithm based on Bayesian theory can meet the denoising demand of mobile phone images because of its rapidity, validity and so on. However, denoising by wavelet transform is optimal for Gaussian noise, and the actual noise of images taken by mobile phones does not completely conform to Gaussian distribution, and then a down-sampling method is adopted to simulate the Gaussian noise. In this article, according to the actual requirements of mobile phone image denoising, an adaptive denoising method for colour images of mobile phones based on bivariate shrinkage function is proposed. Firstly, the actual image noise was made similar to the Gaussian noise by the down-sampling method, and then a kind of adaptive noise variance of the bivariate shrinkage function based on Bayesian denoising method is proposed to estimate the variance of the down-sampled image. Finally, the denoised image was grayed to further eliminate the noise in the flat areas. Simulation and actual experimental results showed that the method of this paper can get better denoising effect than other methods.
    Keywords: mobile phone image; denoising; down-sampling; bivariate shrinkage function; noise variance; graying

Special Issue on: ICICS 2016 Advances in Humanised Computing Systems and their Applications

  • A system for application development using aerial robots   Order a copy of this article
    by Mohammad Fraiwan, Ahmad Alsaleem, Hashem Abandeh, Omar Al-Jarrah 
    Abstract: Autonomous airborne systems have generated a lot of interest in civilian as well as military applications. The application development process for such systems is inherently expensive and is prone to costly errors. The majority of the developed applications involve routing and navigation toward targets coupled with obstacle avoidance. In this paper, we present the approach and algorithms that were employed to tackle the routing and avoidance problems. The proposed solutions were applied to land-based robots as well as a quad-rotor aerial system. The quad-rotor flight path navigation and routing was programmed based on GPS and on-board measurement data. Obstacle avoidance was implemented based on an algorithm that relies on the idea of a virtual potential field. Kalman filters were implemented to improve the accuracy of the measured data, while 3D visualisation was used to visually identify obstacles. In the case of in-building reconnaissance, where GPS signals are very weak and largely useless, data from laser sensors and proximity feeds was aggregated and processed to identify obstacles and the topology of the surrounding environment. The organisation and interaction of these various modules is described in detail.
    Keywords: quad-rotor; obstacle avoidance; Kalman filter; maps; potential field.

  • Petri net-based verification of security protocol implementation in software evolution   Order a copy of this article
    by Mohd Anuaruddin Bin Ahmadon, Shingo Yamaguchi, Brij Gupta 
    Abstract: Implementation of security protocols in software plays an important role to protect the whole system from vulnerabilities. In order to protect the system from new threats, software needs to adapt to new security requirements. Thus security upgrades and patches are implemented to the software. Previous works only focus on logical correctness of security protocols, but we focus on the successful implementation of security protocols in a program. A program evolves as programmers apply security patches to its source code. Hence, the process of verifying important security protocol implementation is difficult. In this paper, we propose model-driven security verification throughout software evolution. It consists of two major methods: (i) a reverse engineering method to translate a program into a Petri net model; and (ii) a model-driven verification method to confirm that the security protocol implementation is valid. Concretely, for a program X that implements a security protocol specification A, does its derivation Y also implement A? The answer is yes if Y inherits the behaviour of X. We applied behavioural inheritance analysis to verify security protocol implementation. We also illustrated the methods with an example in software evolution.
    Keywords: software evolution; reverse engineering; security protocol; Petri net; behavioural inheritance.

  • Knowledge-based auto-configuration system using ubiquitous robotics for services delivery in smart homes   Order a copy of this article
    by Mustafa Al-Khawaldeh, Xi Chen, Philip Moore, Ibrahim Al-Naimi 
    Abstract: The wide availability of services and devices within contemporary smart home environments make their management a challenging and rewarding task. Maintaining complex smart home systems throughout their lifecycle entails considerable resources and effort. These challenges have stimulated the need for dynamic auto-configurable services amongst such distributed systems. This research aims to devise methods to automate the activities associated with customised service delivery for dynamic home environments by exploiting recent advances in the field of ubiquitous robotics and Semantic Web technologies. It introduces a novel approach called the Knowledge-based Auto-configuration Ubiquitous Robotics for Smart Home Environments, which uses the Sobot to achieve auto-configuration of the system. A proof-of-concept testbed has been designed, implemented and validated via several case studies. The results show that the Sobot is capable of creating and executing new or alternative feasible configurations to meet the systems goal by using inferred facts based on the smart home ontological model, so that the system can adapt to the changed environment.
    Keywords: smart home; ubiquitous robotics; service delivery; Semantic Web; knowledge-based auto-configuration systems.

Special Issue on: Learning for Robotics

  • Conditional proxy broadcast re-encryption with fine grain policy scheme for cloud data sharing   Order a copy of this article
    by Sun Maosheng, Ge Chunpeng, Fang Liming, Wang Jiandong 
    Abstract: Conditional proxy broadcast re-encryption (CPBRE) enables a semi-trusted proxy to convert Alice's ciphertext satisfying a certain condition into a set of users' ciphertext. The proxy, however, cannot learn anything about the underlying plaintext. The traditional CPBRE schemes cannot support flexible control on conditions. In this paper, we present a new primitive named conditional proxy broadcast re-encryption with fine grain policy (CPBRE-FG). In a CPBRE-FG scheme, the re-encryption key is generated with an access tree, and the ciphertext is constructed under a set of descriptive conditions. The proxy can convert a ciphertext if and only if the set of conditions satisfies the access tree. We formalise the notion of CPBRE-FG and present an efficient CPBRE-FG scheme. Finally, we prove its effectiveness against chosen-ciphertext attack (CCA) security in the random oracle model.
    Keywords: conditional proxy re-encryption; proxy broadcast re-encryption; access policy; random oracle model.

Special Issue on: IT4OD 2014 Information Technology for Organisation Development

  • An improved CUDA-based hybrid metaheuristic for fast controller of an evolutionary robot   Order a copy of this article
    by Nour EL-Houda Benalia, NourEddine Djedi, Salim Bitam, Nesrine Ouannes, Yves Duthen 
    Abstract: This paper proposes a novel parallel hybrid training approach to conceive an evolutionary robot. The proposed design aims to provide efficient behaviours to perform its tasks in a complex area, such as walking toward a hidden destination. Embedded in the robot brain, this training and evolution combination is typically accomplished by evolving considerable Recurrent Neural Networks (RNNs) using an Evolutionary Strategy (ES). The effectiveness of this proposal is improved by employing CUDA technology that executes the evolutionary process of RNNs in a parallel way. The modifications applied are intended to meet CUDA requirements in terms of CPU/GPU cooperation and memory management. Using a set of experiments performed by a GPGPU-based physical simulator named Open Dynamics Engine (ODE) and CUDA-based evolution, the effectiveness of the proposed parallel evolutionary training technique was validated for real movements of humanoid robots. This validation showed a promising speed-up, since this field requires very powerful computational resources.
    Keywords: artificial life, robotics; parallel evolutionary algorithms; recurrent neural network; GPU

Special Issue on: IEEE/IFIP EUC 2013 Embedded and Ubiquitous Computing

  • Energy-efficient analysis with end-to-end delay constraints in wireless sensor networks   Order a copy of this article
    by Gaocai Wang, Xinsheng Yu, Daofeng Li, Jin Ye 
    Abstract: Longer time sleep (low duty cycle) of sensor nodes with sleep-wake mechanism in wireless sensor networks will result in longer delay for transmission of data-collected, although it can reduce the nodes energy consumption and extend its lifetime. Therefore, it is an important and significant topic to balance energy consumption and delay in wireless sensor networks. In this paper, we mainly focus on an energy-efficient mechanism with end-to-end delay constraints. We divide input flows into multiple sub-flows in terms of a configurable weight of links in order to avoid excessive energy consumption of sensor nodes caused by forwarding too much collected data. So, collected data pass through multiple different links and sensor nodes to reach the sink node. We establish an analytic framework for end-to-end delay based on network calculus according to arrival process of flows and service process of sensor nodes. On the other hand, sensor nodes provide rate-latency guaranteed service for arrival flow based on their active time and the maximum capacity of links. The case study and numerical results show that the proposed method can provide an effectively balanced strategy between energy consumption and delay by adjusting the duty cycle of sensor nodes properly in wireless sensor networks.
    Keywords: wireless sensor networks; network calculus; delay; duty cycle; energy consumption