International Journal of Internet Technology and Secured Transactions (73 papers in press)
Managing Incident Response in Industrial Internet of Things
by Allan Cook, Leandros Maglaras, Richard Smith, Helge Janicke
Abstract: Industrial control systems are an essential element of critical national infrastructure, often managing processes and utilities that are essential to a nation's well being and prosperity. These systems are increasingly becoming the target of cyber attacks, and as a result are required to adopt a stronger cyber defense posture. In the next years, the Internet of Things revolution will dramatically alter manufacturing, energy, agriculture, transportation and other industrial sectors of
the economy. Industrial Internet of Things(IIoT) will bring new opportunities to business and society, along with new threats and security risks. However, much of the technology within a control system is based on proprietary devices optimized for performance at the expense of security and does not necessarily integrate well into an overall defense-in-depth architecture. Similarly, the control system technology does not readily support the processes and procedures found in IT incident response plans. In this paper we explore the characteristics of an industrial control system and consider them within the framework of an established incident response framework by Prosise at al. We conclude that existing incident response processes are applicable to industrial control systems, but their nature must be modeled, especially in the pre-incident phase of planning, in order to accommodate the idiosyncrasies of such technologies. We recommend that these models be developed and tested within synthetic environments to test and quantify cyber attack impacts and drive architectural improvements and incident response investment.
Keywords: Incident Response; Industrial Control Systems; Industrial Internet of Things.
TAACS-FL: Trust Aware Access Control System using Fuzzy Logic for Internet of Things
by Thirukkumaran Raman, Muthukannan P
Abstract: The Internet of Things (IoT) is technological revolution that has recently become more important to the real world because of the growth of smart devices, embedded and ubiquitous communication technologies and combined with cyber world to provide many smart services. These services are particularly creating new challenges in security and privacy concerns. To address this issue Trust management system and Access control system must be focused in IoT. This paper presents a Trust Aware Access control system using Fuzzy Logic (TAACS-FL) for IoT. Access control is an important mechanism to ensure only trusted users/devices access the data from the sensor device or command the actuators to perform some task in the IoT context. First we monitor the devices and gather the trust parameters like Successful Forward Ratio (SFR), Data Integrity (DI) and Energy Consumption Rate (ECR). Second, by using fuzzy engine trust parameters are combined and overall trust value is calculated. Third, based on the trust value access control method is defined.NS-2 based simulation result shows TAACS-FL guarantees scalability and energy efficient.
Keywords: Internet of Things; Trust; Access control; Security; Fuzzy; Cluster.
A dependable and lightweight trust proliferation approach for the collaborative IoT systems
by Hayet Benkerrou, Mawloud Omar, Fatah Bouchebbah, Younes Ait-Mouhoub
Abstract: Trust and reputation evaluation in the Internet of Things (IoT) constitutes nowadays a major challenge that is still attracting the research community to work on and investigate. The IoT with its widely heterogeneous objects requires collaborative computation to perform heavy cryptographic operations in the most constrained resource devices. Indeed, the effectiveness of the trust and reputation assessment plays an important role for selecting the best collaborators. In this paper, we propose a dependable and lightweight trust proliferation approach for the collaborative IoT systems. By recording the malicious tasks which could be performed during the service execution, our approach introduces a new derivation of direct trust. Furthermore, it combines dynamically the direct and indirect trust evaluation to ensure more trustworthiness and reliability in the selection of the best collaborator objects. Through the simulations, we show that our trust derivation approach achieves high accuracy in the selection of efficient and confident collaborators.
Keywords: Internet of Things; Trust; Reputation; Security; Collaboration.
Variable Switching Frequency Control for Active Cell Balancing Systems
by SANGWON LEE, JAEJUNG YUN
Abstract: A new active cell balancing control method is presented for improving the active cell balancing speed of a Li-ion battery pack. The proposed method calculates the switching frequency based on the sensed charging/discharging current of the battery pack. It then modulates the balancing power of the active cell balancing circuit within the value of the charging current limit and discharging current limit. The method can achieve high balancing performance without much computational work and additional power electronic components. A multi-cell balancing algorithm is also introduced for using the proposed method in an actual battery management system, which was verified by PSIM simulations with an irregular profile of the battery load current. The proposed method shows faster balancing speed than a conventional cell balancing method with a fixed switching frequency.
Keywords: Li-ion battery; Buck-boost converter; Cell balancing; Variable switching frequency.
WebRTC Security Measures and Weaknesses
by Ben Feher, Lior Sidi, Asaf Shabtai, Rami Puzis, Leonardas Marozas
Abstract: WebRTC is a technology that enables real-time communication between Web browsers for information streaming, including text, sound or direct data transfer. WebRTC is supported by all major browsers and has a flexible underlying infrastructure. In this study, we review current state of WebRTC and analyse security shortcomings during acts of communication disruption, modification, and eavesdropping. In addition, we examine WebRTC security in experimental scenarios.
Keywords: WebRTC; attack patterns; browser streaming; telecommunication services; lawful interception; security; weaknesses; mitigation.
Trust Assessment of X.509 Certificate Based on Certificate Authority Trustworthiness and its Certificate Policy
by Zakia El Uahhabi, Hanan El Bakkali
Abstract: Nowadays, X.509 certificate is largely used to prove its holder identity in open networks. Then, the Relying Party (RP) needs an automated mechanism for evaluating its trustworthiness in order to decide whether to accept it or not. In this context, we provide him with this mechanism allowing him to decide if he should trust in a received certificate or not. In our previous work, we have proposed an architecture for calculating a certificate trust level. Using a defined algorithm, this level is computed depending on three parameters: the calculated trust level of certificate authority (CA), the certificate policy quality, and the rating of the certificate fields. In this paper, we improve the algorithm used to calculate a CA trust level on the basis of trust level of the CAs that had issued certificates for it and their extension fields. By this way, the calculated trust level reflects a real trustworthiness of certificate because it is computed on the basis of the real factors inﬂuencing this trustworthiness. It is then more relevant for a relying party when deciding whether to accept a received certificate or not.
Keywords: certificate authority; PKI; reputation score; trust level; X.509 certificate; public key infrastructure.
Anti-Continuous Collisions User Based Unpredictable Iterative Password Salted Hash Encryption
by Ali Al Farawn, Nabeel Salih Ali, Munqath Alattar
Abstract: Recently, providing services remotely over a network to enhance functionality and usability has become a trend. Applications regularly contain sensitive and personal information that should be managed and controlled by authorised persons. Thus, keeping the password security is important to prevent unauthorised users from impersonating other legal users. Hashing the password is one of the safety methods and means of preventing attacks. In this study, we proposed an iterative salted hash encryption mechanism named anti-continuous collision salted hash encryption (ACCSHE) that uses cryptographically secure pseudo random number generator (CSPRNG) and hashed with password data by secured hashing algorithm (SHA-256). The outcome manifests a flexibility of changing the results by controlling several key features, such as salt used,the range of the hashing process iterations or the minimum number of iterations
without affecting the systems usability. The system efficiently prevented continues collision issue and effective processing time cost for an attacker.
Keywords: password encryption; authentication; hashing cryptography;collision; salted hashed; iterative hashing.
Intrusion Detection Model using Feature Extraction and LPBoost Technique
by I. Sumaiya Thaseen, Ch. Aswani Kumar
Abstract: Purpose - A lot of intrusion and hacking events are surrounding the internet domain, bringing in a need for security systems. Intrusion Detection System (IDS) safeguards the network from any attack by continuous monitoring of the system activities. The major issue for any intrusion detection model is to identify anomalies with maximum accuracy and minimal false alarms.
Design/Methodology/Approach - An intrusion detection model is developed combining chi-square feature selection and LPBoost algorithm. Chi-square feature selection is deployed to build the optimal features as the network traffic data consists of many attributes. The optimum features are utilized by the LPBoost algorithm for recognizing the regular traffic and diverse attacks in the network. An ensemble classifier is chosen as they typically outperform a single classifier.
Findings - The investigational analysis is performed using NSL-KDD and UNSW-NB data sets. The experiments clearly show that the hybrid model achieves a higher detection and reduced false positive rate in contrast to other techniques.
Originality/Value- The key contribution of the model is the feature extraction and optimization of the ensemble parameter for improved accuracy of the model. Feature extraction minimizes the computation time and only essential features required for classification are retained in the sample set. The optimization of trade-off parameter in the ensemble ensures the desirable cross-validation accuracy is achieved. The model is tested on recent attacks present in the UNSW-NB dataset.
Keywords: Boosting; Chi-Square; Ensemble; Feature Selection; Intrusion Detection; Linear Programming.
Storage and Query Over Encrypted Sensitive Association Rules in Database
by Meenakshi Bansal, Dinesh Grover, Dhiraj Sharma
Abstract: In this modern era of increasing need of data sharing along with data security, processing over encrypted data is highly desirable. Data encryption is the most common technique used for maintaining the data privacy. However,when processing is required to be done on this encrypted data it becomes a critical task. In most of the existing theories data need to be decrypted before it is being processed. Decryption before processing leads to serious threat to data. To avoid this, a new mechanism has been proposed and implemented which provides strong data protection. This mechanism helps to query over encrypted data without decrypting it. Experimental results show that the new technique outperforms the existing one in terms of query performance, computation time and storage memory.
Keywords: query; encryption; database; decryption; security; key mapping; elliptic curve cryptography; ECC; sensitivity; association rules; storage.
Secure RSA implementation against horizontal correlation power analysis attack
by Jaecheol Ha, Dongwon Park, Soungwook Choi
Abstract: Since passive leakage information analysis and active fault injection attacks on naive implementation of the RSA (Rivest, Shamir, and Adelman) cryptosystem can be used to retrieve a secret key, several countermeasures against these attacks have been developed. In this paper, we point out that the HCPA(Horizontal Correlation Power Analysis) attack can be applied to the square-multiply ladder exponentiation algorithm and its variants, which are used for secure RSA implementation. Furthermore, we propose a novel exponentiation algorithm to defeat previous implementation attacks, as well as the HCPA attack, in particular. This algorithm is designed to overcome weakness against the HCPA attack by adopting an intermediate message update technique based on an extended modulus. We can employ the proposed exponentiation algorithm to implement a secure CRT-RSA (Chinese remainder theorem based RSA) cryptosystem by thwarting the Bellcore attack.
Keywords: RSA cryptosystem; side channel analysis; fault attack; horizontal correlation power analysis attack.
ERAC-MAC Efficient Revocable Access Control for Multi-Authority Cloud storage system
by Sudha Senthilkumar, Madhu Viswanatham
Abstract: Abstract: In the recent scenario, there is an appreciable escalation in the utilization of cloud computing by critical industrial applications due to its cost-effective storage and computing. However, due to an unreliable server in a cloud, the access control turns out to be the challenging issue to ensure the confidentiality of sensitive data. The Ciphertext Policy Attribute Based Encryption (CP-ABE) is deliberated to be an apt technique to enforce the access control for encrypted cloud outsourced data. But, due to the computation complexity of decryption, user revocation and complexity of key management for achieving granularity, prevailing CP-ABE schemes when applied directly to multi authority attribute system, incurs more computational costs in the order of NP. In this paper, an efficient CP-ABE based multi authority attribute system is put forth that supports decryption and user revocation by CSP with the advent of a blind encryption/decryption technique and a novel coloring scheme for predicting user behavior analysis. Security and Performance of ERAC-MAC was analyzed and found to be much better than the other prevailing schemes. The implementation was done using the paring based cryptography library of the Stanford University in Ubuntu environment.
Keywords: Ciphertext Policy Attribute Based Encryption; Attribute Revocation; Attribute Authority; Multi Attribute Authority.
A Novel Data Aware Task Clustering Mechanism for Scientific Workflow Applications in Cloud
by Soma Prathibha, B. Latha, G. Sumathi
Abstract: Scientific applications modeled as Directed Acyclic Graphs (DAG) are composed of complex calculations and a large amount of data transfer. It is very difficult to execute these applications in traditional distributed computing platforms. For such applications cloud provides a reliable solution due to its unique characteristics such as availability of heterogeneous resources, on-demand provisioning, pay-per-use. For effective provisioning of resources and to improve the performance, task clustering is performed which combines two or more tasks into a single executable unit. Task clustering can help to reduce the system overheads such as queue delay, engine delay and so on. Existing clustering algorithms in this domain focus more on computational granularity of the tasks without considering the data dependency among the tasks. In this paper, a data aware clustering algorithm has been proposed which combines the tasks depending on the size of data transferred between interdependent tasks. Experiments were conducted to compare the proposed clustering algorithm with the existing baseline and balanced clustering algorithms and it was observed that proposed algorithm gave better makespan and cost for data intensive workflow applications.
Keywords: Directed Acyclic Graphs(DAG); Cloud Computing; Task clustering; Billing model; Scheduling.
REVIEW OF CYBER ATTACKS CLASSIFICATIONS AND THREATS ANALYSIS IN CYBER-PHYSICAL SYSTEMS
by MOHAMMED NASSER AL-MHIQANI, Rabiah Ahmad, Zaheera Zainal Abidin, Nabeel Salih Ali, Karrar Hameed Abdulkareem
Abstract: Cyber-Physical Systems (CPSs) are the systems that have an interaction between the computers and the real world. CPS has been widely used in many different areas and played a significant role in our daily lives. Smart grid, healthcare, aircraft, and emergency management are the most areas where CPS applied. However, the cyber-physical systems currently are one of the critical hackers targets that have a lot of incidents because of the high impacts of these systems. Several works have been conducted in CPS, but still, there is a lack of theories and tools that organizations and researchers can use to understand the nature of the new threats and the impacts that each danger can cause to the physical systems. Hence, when one of these keys for cyberinfrastructure systems is attacked, the same consequences exist for a natural disaster or terrorist attack. This article provides a brief description of cyber-physical systems usage areas and security challenges in some of the critical CPS fields. Likewise, discusses the frameworks and taxonomies that have been used for classifying cyber-attacks or incidents. As well, study and analyse threats that have been stated in the previous studies and research to understand the current status of the risks on CPS.
Keywords: Cyber-Physical Systems; Cyber-Attacks; CPS Security Challenges; Incidents; Threats Analysis.
Comparison of Security Related Methods in Open Interconnect Consortium (OIC) and one Machine-to-Machine (oneM2M) for Security Interoperability
by Dong In Kim, Hyungu Lee, Jaehwan Lee, Goutham Reddy Alavalapati, Ji Sun Shin
Abstract: The services and applications of the Internet of Things (IoT) support various areas such as smart home, smart car and so on. Recently, several groups of companies have been trying to integrate and standardize the IoT platforms and two major platforms among them are one Machine-to-Machine (oneM2M) and the Open Interconnect Consortium (OIC). oneM2M and OIC standards enable connected devices to communicate each other regardless of their manufacturers and operating systems. Also, there are attempts to interwork two open platforms. However, security interoperability has been less focused in the interworking. In this paper, we present the comparison of security related methods between oneM2M and OIC standard specifications for the security interoperability. We compare the basic concepts and terminology of two standards by clarifying the same-spelled basic terms with different meanings and different terms having similar concepts.
Keywords: Open Interconnect Consortium (OIC); Security; Internet of Things (IoT); Interworking.
Efficient user authentication, server allocation and secure data storage in cloud
by MANOJ TYAGI, Manish Manoria, Bharat Mishra
Abstract: With the increased popularity and the need to store the sensitive data over the cloud, the security of stored data is a very big challenge. This work has not only investigated and rectified the susceptibility of the data in the cloud, but also proposed the technique for user authentication and server allocation efficiently. Cuckoo Search Algorithm (CSA) is applied for efficiently allocating the server. For maintaining the privacy of clients data over the cloud, Improved Attribute Based Encryption (IABE) can effectively do attribute adjunction/revocation, reduce the time complexity as well as safeguard from collusion attacks. The minimum set generation, proxy key generation, file updation, and secret key updation, is modified for efficient attribute revocation/adjunction. The combination of IABE with CSA achieves the security objective and the process is enhanced efficiently.
Keywords: Cloud computing; Encryption; Decryption; Secure data Transmission; Secure storage; Attribute revocation; Server allocation; Cuckoo search algorithm; IABE.
A Secure and Robust Smart Card Based Remote User Authentication Scheme
by Katayon Dowlatshah, Mojtaba Alizadeh, Mehrdad Ahmadzadeh Raji
Abstract: In new era of technology, smart cards play a critical role in economic and social interactions. Security vulnerabilities of these smart is a main concern for users and tech experts. Authentication as one of the basic security solution is used to protect the data from unauthorized access. In recent years, research on smart card-based password authentication get more attention. This paper, reviews different smart card authentication methods and proposes an improvement of the Yassin et al.  scheme to cover its security weaknesses like session key attack vulnerability. Finally, the proposed method is analyzed and compared to the related works.
Keywords: Smart card; authentication; impersonation; server; session key.
An exhaustive study of DDOS attacks and DDOS Datasets
by Joshua Nehinbe, Solomon Onyeabor
Abstract: Conceptually, frequent Distributed Denial of Service (DDOS) attacks on corporate networks are serious challenges that are recently demanding urgent explanations. The attacks destroy and deny users from accessing computer and mobile networks. Consequently, several organizations have lost long-standing reputations they have built over time. Some firms have also incurred huge financial resources, reduction in the numbers of customers and annual patronage within a short space of the attacks. Unfortunately, experiences learned by victims are not often made public. Besides, the strengths and weaknesses of the available DDOS traces are not recently discussed in contemporary literatures. Therefore, feelers have begun to question and ponder about the resolute and validity of the existing models despite the fact that they were duly evaluated with some standard DDOS datasets. Thus, this paper discusses the rudiments of DDOS attacks and elaborately explicates some of the challenges associated with DDOS datasets. We use C++ programming language to empirically demonstrate potential datasets that researchers can adopt to investigate DDOS attacks. The results suggest that researchers can secure informative DDOS datasets by merging different DDOS datasets together. Finally, the review will be helpful to investigators, analysts, data donors and litigators in the determination and enforcement of legal rights against intruders.
Keywords: Distributed Denial of Service (DDOS); Intrusion; Intrusion Detection System (IDS)Intrusion Prevention System (IPS); datasets.
Performance evaluation for the hash generation phase of a democratic blockchain
by Luis Lugo, Cesar Pedraza
Abstract: Distributed Ledger Technologies (DLTs) have the potential to transform different areas of research and industry. Initially created to support a peer-to-peer electronic cash system -- more commonly known as bitcoin -- blockchains provide a decentralized transactions and data management technology. This decentralized technology is secure, anonymous, and transparent. Nonetheless, the blockchain protocol has a number of technical weaknesses such as power computing dependency and high power consumption. An alternative protocol proposes a democratic approach in which the computing power is not a determinant factor in user participation. The democratic protocol has three phases: hash generation, hash broadcast, and hash validation. We evaluate the performance of the hash generation phase on CPU, GPU and cluster platforms. A considerable speedup is achieved with GPUs when using final nonce values similar to a real blockchain application. Also, it provides the best power efficiency.
Keywords: Distributed Ledger Technology; Hash generation; Parallel computingrn.
Key-Dependent Permutation Layer Based on Two Dimensional Discretized Chaotic Maps for Lightweight Block Ciphers
by Hue Ta Thi Kim
Abstract: This paper proposes a design of a key-dependent permutation layer. Based on the comparison of the properties for different two-dimensional discretized chaotic maps, the Standard map is chosen with good diffusion properties to construct a chaos-based permutation layer in block ciphers. The proposed construction has both high security strength and hardware efficiency. The result of the hardware implementation shows that it is suitable for lightweight block ciphers due to its low resource utilization.
Keywords: Chaos-based cryptography; Lightweight block cipher; Key-dependent; Permutation layer.
Special Issue on: IoT Services for Trustworthy Secured Crowd Sourcing Applications
An Integrated Approach For Network Traffic Analysis Using Unsupervised Clustering And Supervised Classification
by Chokkanathan Kothandapani
Abstract: Traffic classification and analysis is a significant task to control the network traffic in a heterogeneous manner. The unsupervised learning system or network environment fails to expand the supervised classification model for network analysis. The several data mining techniques identified the network traffic pattern and classified the network traffic accurately using unsupervised learning approach. However, the continuous evaluation of network traffic on multi-dimensional data is a difficult task in real time data traffic. In order to overcome the problem in traffic analysis, An Integrated K-means Unsupervised Clustering and Supervised C4.5 Classification (KUC-SC) technique is introduced. An integrated technique is used to evaluate the network traffic conditions to classify the patterns of real time and non-real time traffic. An integrated KUC-SC technique performs two types of processing steps such as clustering and classification. At first, K means unsupervised learning algorithms is applied in KUC-SC technique to form a k number of clusters using the different input data point with the nearest mean. The clustering approach is used for classifying the given data. After that, C4.5 is used to classify the data whether it is real time or non-real time traffic through the construction of decision-tree. At every node of the tree, C4.5 algorithm classifies the data point that most efficiently divides the set of samples into subsets with similar characteristics. This in turn improves the classification accuracy in network traffic data analysis. An experimental result shows that the proposed KUC-SC technique obtains the better performance in terms of classification accuracy, classification time, true positive rate and communication overhead compared to the state-of-the-art works.
Keywords: K-means Unsupervised Clustering; Supervised C4.5 Classification; real time and non-real time traffic analysis.
Response Time Based Resource Allocation According to Service Level Agreements in Cloud Computing
by G. Hemanth Kumar Yadav, K. Madhavi
Abstract: Cloud computing is a technology which offers various services as and when required by the user through various cloud providers. The scalable nature of cloud has made it to reach various domains and have a strong root in every organization. The resource provisioning has become a challenging task for many cloud providers. This work proposes an efficient framework for handling storage, application and computation services, offering Service-Level Agreements (SLA) backed performance and uptime promises for their services in cloud computing .Further this tries to benefit both the users as well as cloud providers by enhancing the features for the customers and by gaining profit for the providers. The proposed SLA based resource provisioning system is found to perform better than the existing other resource provisioning systems in terms of response time and other QoS parameters.
Keywords: Cloud computing; Resource Allocation; Service level agreement.
Special Issue on: Recent Technologies for Networking and Advanced Systems
Virtual Network Functions Placement System for 5G Mobile Network Architecture
by Sara Retal, Abdellah Idrissi
Abstract: The mobile telecommunications market is experiencing new trends
taking advantage of network virtualization and Cloud Computing techniques.
This article advances one of the most crucial challenges which is the placement
of virtual network functions over the Cloud. In this vein, we propose a virtual
network functions placement system which is designed to have the maximum
level of flexibility for meeting the operators preferences and adjusting to the
users behavior. The system finds a fair solution respecting the constraints
conforming with the 3GPP standards which are minimizing Serving Gateways
relocations cost and the cost of the path between Packet Data Network Gateways
and eNodeB base stations. Furthermore, the system aims at reducing the incurred
cost of virtual machines. The proposed approach to implement the system solver
is Constraint Programming and is compared to Boolean Satisfiability, and Game
Theory approaches. The proposed system solver is evaluated through computer
simulations, and encouraging results are obtained.
Keywords: 5G Mobile Network Architecture; Virtual Network Functions Placement; Constraint Programming; Multi-objective Optimization.
A New Model for Communities' Detection in Dynamic Social Networks Inspired From Human Families.
by Rachid Djerbi, Mourad Amad, Rabah Imache
Abstract: Nowadays, social networks have been widely used by different people for different purposes in the world. The discovering of communities is a widespread subject in the space of social networks analysis. Many interesting solutions have been proposed in the literature. However, most solutions have common problems: the stability and the community structures quality. In this paper, we propose a new model to find communities based on a new concept called
Keywords: dynamic social networks; community detection; communities overlap; large families; quality of community structures; stability.
Industrial Internet of Things over IEEE 802.15.4 TSCH networks: Design & Challenges
by Mohamed Mohamadi, Badis Djamaa, Mustapha Reda Senouci
Abstract: Using Internet of Things technologies in manufacturing provides a promising opportunity to build powerful industrial systems and applications. The quest for mobility, flexibility, and low-energy consumption has created a strong push toward using low-power wireless solutions to enable the Industrial Internet of Things (IIoT). This paper presents a survey of the emerging research concerning IIoT with a focus on the most promising solutions. It, first, outlines the main requirements to be addressed in order to build a powerful IIoT system. The paper, then, presents an overview accompanied by a comparative study of the most prevalent IIoT communication technologies. The study reveals the potential of the IEEE 802.15.4 standard with its Time Slotted Channel Hopping (TSCH) mode to lead the way through the IIoT, thanks to its latency, reliability and low-power characteristics along with the support of multi-hop communications. Based on this outcome, the paper provides an in-depth look at TSCH mechanisms and outlines the most challenging issues. Finally, the paper concludes the need to propose new solutions addressing such issues in order to make successful IIoT systems.
Keywords: IEEE 802.15.4e; Time Slotted Channel Hopping; Scheduling; Internet of Things; Industrial Internet of Things; Low power and Lossy Networks; Communication technologies.
Special Issue on: Big Data Analytics and Deep Learning Methods for Secure Data Transmission in Edge Computing, Internet of Things and Cloud Computing
Analysing Thalamus and its Sub nuclei in MRI Brain image to distinguish Schizophrenia subjects using back propagation neural network
by ArivuSelvan K, Sathiya Moorthy E
Abstract: In this paper we presented precise and proficient techniques for measuring the human thalamus, medial dorsal and the pulvinar nucleus with magnetic resonance image (MRI). In spite of the fact that thalamic nuclei are not straightforwardly visible on traditional MRI image, it is conceivable to watch contrasts between the nuclei using Diffusion tensor imaging (DTI). We applied a novel and competent image pre-processing techniques to enhance the visual quality of MRI image. In addition to this we have used various segmentation algorithms to accurately extract entire thalamus from brain MRI images. Diffusion MRI is used to extract various nucleus of thalamus. Several optimal features such as textures, morphological are derived from thalamus and medial dorsal regions which are then used to train the artificial neural network model (ANN). Our artificial neural network model accurately classifies between schizophrenic and healthy subjects based on thalamic anatomy for larger sample sizes.
Keywords: Thalamus; Artificial neural networks; MRI; Schizophrenia; GLCM;Sobel; Level set; Fast marching.
A Public Key based Encryption and Signature Verification Model for Secured Image Transmission in Network
by JAYANTHI RAMASAMY, Johnsingh Kumaresan
Abstract: Image transmission is a challenging task due to the large file size and the security issues. Medical images are communicated through internet from the laboratories to the hospitals for analysis and treatment. The performance of such transmission is affected based on the size of the image files which are transmitted. Hence, it is necessary to compress the medical images while sending and to decompress them at the receiver side. Moreover, the sensitiveness of medical applications needs to apply only lossless compression techniques so that the diagnosis will be accurate. The security issues pertaining to medical images including privacy and prevention of attacks can be tackled by performing user authentication and encryption of medical images. Most of the existing systems on medical image transmission use symmetric key cryptography where the key is shared to multiple recipients leading to security leakage. This has been addressed by applying public key encryption schemes. However, a secured communication technique which uses compression, user authentication and encryption / decryption is more powerful than the existing systems on medical image transmission. Therefore, a new secured transmission algorithm which performs compression using Singular Value Decomposition (SVD), user authentication using digital signatures and encryption/decryption using AES and RSA algorithms for image encryption and Hill-Cipher for data encryption which are coordinated using intelligent agents for communication and rules for decision making is proposed in this paper. The major advantages of the proposed model include fast transmission, increase in security and non-loss compression and decompression and intelligent decision making on medical image transmission.
Keywords: Compression; Security; Encryption; Decryption; Image Transmission; Intelligent Agents; Authentication; Publickey Cryptography;.
Special Issue on: ICCE 2017 Recent Advances on Consumer Electronics
An intelligent emergency rescue assistance system for mountaineers
by Shih-Hsiung Lee, Cheng-Yao Hsu, Chu-Sing Yang
Abstract: Mountaineering is one of main recreational activities of modern people. The mountain accidents include mountain sickness, hypothermia, missing, accidental fall and so on. This paper proposes an intelligent emergency rescue assisted mountaineering system, including a wearable device and a management platform. The physiological signals are monitored for mountain sickness and hypothermia, asking the user to take precautionary measures in advance. In the missing and accidental fall scenarios, the search and rescue team is provided with timely information, and the wearable device is switched to emergency beacon signal automatically, helpful to increase the efficiency of search and rescue. Added to this, the mobile device is integrated with Blue tooth, the mobile device can send the geo information and the information on the wearable device to the management system by means of its communication capability. When an accident happens, the mobile device and wearable device send the beacon signal crosswise, the power usage rate is maximized effectively, the search and rescue time is prolonged. This system architecture effectively prevents mountain accidents, indicates the location and informs related units to provide emergency rescue at the soonest.
Keywords: Hiking; Search and Rescue; Wearable Device; Internet of Things; Beacon Signal.
Blind Spot Monitoring at Night-time using Rear-View Camera
by Seon-Geol Kim, Kang Yi, Kyeong-Hoon Jung
Abstract: The Blind Spot Monitoring (BSM) is one of the key functions of Advanced Driver Assistance System (ADAS). In this paper, we propose a vision-based blind spot detection and tracking algorithm which is applicable at night-time. The feature of highly bright blobs due to the headlights of behind vehicle is employed for the detection of vehicles in blind spot area, because the appearance-based approach that can be used at daytime is not any more appropriate. We calculate the motion vectors of detected blobs to find an approaching vehicle and make headlight pairing to estimate its position by use of the projection map. We can successfully generate an alarm signal by detection and tracking the overtaking vehicle in blind spot area at night-time.
Keywords: ADAS; BSM; vehicle detection; projection map.
An Auto-Configuring Mesh Protocol with Proactive Source Routing for Bluetooth Low Energy
by Julio León, Abel Dueñas, Cibele Makluf, Frank Cabello, Guillermo Kemper, Yuzo Iano
Abstract: The Internet of Things (IoT) is spreading rapidly towards creating smart environments. Wireless sensor networks (WSN) are among the most popular applications discussed in IoT literature, with most of them considering many forms of wireless mesh communications. One of the most available and popular wireless technologies for short-range operations (yet not designed for mesh) is Bluetooth. Literature shows some studies on mesh networks BLE, based on Bluetooth 4.1 (which supports Master/Slave Multirole). Those approaches require more powerful hardware than a simple wireless sensor peripheral.rnNonetheless, none address dynamic address allocation and topology mapping for BLE. rnWe propose a new autoconfiguring dynamic address allocation scheme for a BLE Ad-Hoc network, and a network map discovery mechanism that doesn't require role changing, compatible with BLE 4.0 or later versions.
Keywords: Bluetooth Low Energy; Mesh; WSN; Proactive Source Routing; Auto-configuring.
Light Field Compression on Sliced Lenslet Array
by Cristian Perra, Daniele Giusto
Abstract: Recent advances in light field technologies is fostering the research
and development of novel imaging applications. Such applications perform
processing of the light field information to create new visual effects such as, for
example, refocusing, perspective change, colour adjustment. Light field
imaging is very data intensive compared with usual digital photographic
imaging, and novel compression algorithms are needed for addressing the
problem of light field storage and transmission. Raw digital light field images
exhibit low spatial correlation if compared to regular images and hence the
performance in terms of rate-distortion of current state-of-the-art image
encoders can be superseded by devising novel image compression
architectures. In this paper, an architecture for lossy compression of unfocused
light field images is proposed. Raw light fields are preprocessed by
demosaicing, devignetting and slicing of the raw lenslet array image. The slices
are then compressed with the JPEG 2000 image coding standard. The
performance of the proposed method is compared against direct application of
JPEG 2000 compression on the 4D light field. The experimental analysis has
been conducted under a set of different compression ratios and the obtained
results show that the proposed method outperforms direct application of the
Keywords: light field compression; raw light field; plenoptic image; sliced
lenslet array; sub-aperture image; JPEG2000 compression; wavelet
compression; light field interpolation; objective quality evaluation; peak signalto-
noise ratio; PSNR; structural similarity index; SSIM.
Special Issue on: ICRTCCM'17 Intelligent Machine Learning Algorithms for High Performance Computing
Design and Analysis of Smart Card based Authentication Scheme for Secure Transactions
by Akshat Pradhan, Marimuthu Karuppiah, Niranchana R, Asha Jerlin M, Rajkumar S
Abstract: Remote authentication scheme utilizing smart cards have become a prevalent concept due to their convenience and simplicity. Recently, Lee et al. proposed a low cost authentication scheme without verifier tables. However, in this paper we show that Lees scheme is susceptible to various attacks andrnfails to provide essential security properties. We then present our own scheme and perform an informal analysis to substantiate the claim that our scheme is able to resist the previous schemes weaknesses.
Keywords: User Anonymity; Offline password guessing attack; Smart Card; User impersonation attack; Forgery attack.
SECURE GEOSPATIAL DATA STORAGE USING SPATIALHADOOP FRAMEWORK IN CLOUD ENVIRONMENT
by Karthi Shankar, Prabu S
Abstract: Advancement in satellite remote sensing technology, leads to growth in data exponentially. Managing complex data for have been made reasonable and simpler by Geospatial Information Systems (GIS) by means of cloud employment. Processed geospatial data is stored in public cloud via secured platform. Main objective of this paper is to propose efficient way of storing geospatial data using spatial Hadoop mechanism in cloud environment. Excessive measure request can be achieved by platform with better scalability by spatial Hadoop GIS.
Keywords: Geospatial Data Storage; Geospatial Information Systems (GIS); Cloud Environment; Authentication; Authorization.
SECURED DATA STORAGE AND AUDITING OF DATA INTEGRITY OVER DYNAMIC DATA IN CLOUD
by Santhosh Kumar P, Latha Parthiban, V. Jegatheeswari
Abstract: Cloud computing is an emerging technology which supports the storage of data via internet. The process of communication is done in an open-access environment and this in turn creates some security and privacy issues which is a real challenge for the cloud users. This facility shoots up the necessity of secure data auditing mechanism over outsourced data. Most of the existing schemes lack the security feature, which can withstand collusion attacks between the cloud server and the unauthorised users. Another most important problem in existing system is data integrity. This paper presents a technique to overthrow the collusion attacks and the data auditing mechanism is achieved by means of vector commitment and backward unlinkable verifier
local revocation group signature. The proposed work involves double encryption technique to deal with the privacy measures in cloud server. To extend the security measures a single file has been split into different blocks and stored with different file names. These may leads to the ambiguity for the attackers to trace out the original data. The performance of the proposed work is analysed and compared with the existing techniques and the experimental results are observed to be satisfactory in terms of computational and time complexity.
Keywords: cloud computing; data auditing; vector commitment; double encryption; privacy.
Propels in Compiler Construction for Versatile Figuring
by Desurkannadasanr Rajendran
Abstract: This paper shows a compiler machine for adaptable figuring. Our technique assembles the flexibility and comfort in a way that grants to port the structure to different centers with an irrelevant effort. In light of a present arrangement stream, we endeavor to accomplish another tier of handiness in the way of exploring and dividing programs written in C on most hoisted able to be done delineation tier. We show that the examination on this level is more successful than on lower ones as a result of usage of more communicative fabricate of programming. The better examination comes to fruition merged with another Static single assignment based estimation for data way creation might provoke upper game plan nature of the last structure setup
Keywords: equipmentprogramming dividing; versatile frameworks;compiler frameworks; reconfiguration booking;.
Automatic Segmentation of Pathological Region (Tumor and Edema) in High Grade Glioma Multi-sequence MR Images through Voted Prediction from Pixel Level Feature Sets
by Geetha Ramani R, Sivaselvi Krishnamoorthy
Abstract: Automatic region segmentation of brain from the neuroimages is an active research area in the medical domain. Currently, different kinds of Magnetic Resonance Imaging acquisition are performed such that each technique highlights a specific region in the brain making multi-sequence images a better candidate for investigation when compared to single sequence. The abnormal regions (tumor and edema) in glioma images are segmented through hybrid technology involving preprocessing, feature extraction and classification. The extracted features are grouped and random forest procedure is applied on each set and the prediction is obtained that minimizes the randomization. The final prediction of a pixel is obtained by aggregation of individual predictions from feature set through maximum voting which increases the ensembling and improves the outcome appreciably. The average Dice Coefficient of tumor and edema segmentation is 0.96 and 0.94 respectively with 3-fold cross validation. The results show significant improvement when compared to earlier methodologies.
Keywords: Magnetic Resonance Imaging; Brain Tumor Segmentation; Image Analysis; Data Mining; Classification; MICCAI BRATS 2012 Challenge Dataset; Random Forest; Glioma; Tumor; Edema.
Improving Performance an Artificial Bee Colony Optimization on Cloud sim
by SARAVANAN S. SUBRAMANIYAN, Gokulraj P
Abstract: The major aspire of this proposed Improved Weis to identify an accurate data search and also to generate data that comes from anywhere. Furthermore, the data itself may be too large to store on a single machine such that the computers are inter connected with each other by the massive internet storage technologies. This approach mainly focuses on design of search engines and its infrastructure grave. Improved Micro partitioning is a modularized approach of cloud computing mainly framed to overcome the pitfalls in the traditional search engine and also in manipulation of large information stored in a single computer. Artificial Bee Colony (ABC) count is an improvement figuring which reenacts the watchful scavenging behaviour of honey bees. In this way in my wander, ABC computation is associated with enhance the arranging of Virtual Machine (VM) on Cloud figuring pre-emptively and in heterogeneous errands. The essential duty of work is to analyze the refinement of Virtual Machine stack conforming count and to reduce the make span of data planning time that is indicate length of the timetable. The arranging framework was replicated using CloudSim gadgets. Exploratory results demonstrated that the blend of the proposed ABC estimation, arranging in perspective of the degree of assignments, and the Longest Job First (LJF) booking figuring played out a better than average execution arranging framework in changing environment and conforming work stack which can diminish the make span of data get ready time.
Keywords: Artificial Bee Colonyrn;Virtual Machine;heterogeneousrn; framework; Cloud computing.
Enhanced Efficient SYN spoofing Detection and Mitigation Scheme for DDoS attack
by Kavisankar Leelasankar, Chellappan C, Venkatesan S, Sivasankar P
Abstract: Protection of critical server from cyber attacks is vital, especially in the case of active attacks like Distributed Denial of Service (DDoS). Attackers start with the Denial of Service (DoS) attack first, since the DoS attack does not need the distributed infrastructure to perform the Distributed Denial of Service (DDoS) attack. A number of attack packets is generated from the single attacking system itself to the victim server, to cause denial of service to the legitimate users. Generally, DoS is an action that prevents or impairs the authorized use of networks, systems, or applications by exhausting the resources, such as central processing units (CPU), memory, bandwidth, and disk space. Seamless services are provided by the constant availability of the server which plays an important factor in providing the customer good Quality of Service (QoS). Monitoring and rate limiting the flow of packets will protect the victim systems by allowing only trusted users during the DDoS attack. The job of the security professionals becomes complex, when the attacks are launched from trusted IP addresses, using Synchronization (SYN) spoofing. The work presented in this paper is experimented with Efficient Spoofed Mitigation Scheme (ESMS) which uses the TCP probing method along with the bloom filter trust model. The experiment is carried out in both IPv4 and IPv6 environment in the SSE (Smart and Secure Environment) real time test bed and the proposed scheme provides accurate and robust information for the detection and controlling of the spoofed packets, during the DDoS attacks.
Keywords: DDoS; ESMS; IP Spoofing; SYN Spoofing; TCP SYN flooding; Trust value.
An Efficient Probabilistic Authentication Scheme for Converging VANET
by HEMAMALINI , Zayaraz , Susmitha Vasanthakumar, Saranya Vadivelu
Abstract: VANET interconnects the vehicles for transferring secure information. In ACPN, the public-key cryptography (PKC) for pseudonym generation is used, which ensures legitimate third parties to achieve the nonrepudiation of vehicles by obtaining vehicles real IDs for privacy preserving authentication and pseudonyms updates on vehicular demands. The convergence point access (CPA) is used to enable communication for out of range vehicles, handover scheme occurs. The scheme provides an seamless connectivity and secure message transmission. However, adversarial nodes could provide false position information. Thus, in VANETs, there is no secure discovery protocol for neighbour positions. We address this problem by designing a distributed protocol that relies on information exchange among one-hop neighbours, we analyse security properties of independent or colluding adversaries, and evaluate its performance using realistic mobility traces. This protocol can be highly effective in detecting falsified position information, while maintaining a low rate of false positive detections.
Keywords: public key cryptography; PKC; convergence point access; CPA; neighbour discovery.
Special Issue on: Cloud Computing, Big Data and Data Science
A Scalable Fine-Grained Analytic Model for Container Cloud Data Centers
by Bingwei Liu, Yu Chen
Abstract: Cloud Computing is today's main-stream computing paradigm because of many attractive features. Although Cloud service providers have deployed numerous large scale Cloud data centers around the world, research in performance modeling for Cloud data centers are still in its infancy. A precise model of a Cloud data center can help the service providers improve their service quality, capacity planning, load balance and reduce operation costs. Most studies in literature focused on modeling hypervisor based cloud, typically IaaS. With the growing popularity of containers in Cloud service providers, there is a need to develop performance models specifically for these systems. A novel Cloud analytic model (CAM) for container-based Cloud data center was proposed. In the model, all schedulers in the Cloud logical hierarchy are modeling as unified Markov Chains with different model inputs. We identified the process at a scheduler as a Quasi-Birth-Death (QBD) process and provided algorithmic solutions using matrix-geometric analytic methods for infinite and finite cases. Physical machines (PMs) are modeled differently due to their underlying characteristics. CAM was able to capture the critical features in the Cloud. We utilized these interactive stochastic models to analyze the performance of the system in terms of mean job delay and probability of job rejection. Finally, a Container emulation framework, ConSim, was developed and tested against the analytic model. ConSim runs on actual container Cloud hardware and measures desired performance matric such as number of rejected jobs and delay of each job. Experimental development using real data were compared with theoretical calculation. The results showed promises in using the proposed analytic model to help service planning in container Clouds.
Keywords: Cloud Computing; container; virtualization; performance modeling; quasi-birth-death process.
DEADLINECREDIT AWARE HEURISTIC FOR DYNAMIC RESOURCE PROVISIONING IN A VIRTUALIZED CLOUD ENVIRONMENT
by Kamali Gupta, Vijay Katiyar
Abstract: Cloud computing as a paradigm has led to its adoption in large scale
parallel processing and distributed computing. The consumer's computational
needs serviced by the providers resulted in significant rise in its demand as latest
services can be accessed with different pricing models, value-added features
and instance types. Resource selection is a tedious task and places momentous
challenges of resource management before consumers and service providers.
As a remedy to this vanguard issue, brokers stipulates resource provisioning
options to ease the task of selecting the best resource that can match the
submitted requests by facilitating a standardized management interface across
Keeping in consideration this point, a Deadline-Aware Sufferage (DSufferage)
algorithm is proposed and implemented at platform level in this research work.
The algorithm is an improvisation in the existing sufferage heuristic. Deadline
parameter has been inculcated to assign precedence levels to the jobs to be
submitted to the machines apart from minimum completion time. The novelty of
the current research study is that the heuristic is centered towards both user and
providers goals in comparison to the existing batch-mode heuristics. The efficacy
of the algorithm has been verified using CloudSim tool and is concluded that
it is proficient enough to allocate resources to users tasks with in constraints of
deadline, resource utilization maximization and SLA violation avoidance.
Keywords: Cloud Computing; Resource Management; Scheduling; Heuristic; Makespan.
Financial Default Payment Predictions Using A Hybrid of Simulated Annealing Heuristics and Extreme Gradient Boosting Machines
by Bichen Zheng
Abstract: Online Peer-to-Peer (P2P) lending platforms face multiple challenges in today's e-commerce, but one of the most outstanding concerns evaluating loan risk based on borrowers' financial status and histories. Traditionally, financial experts assess borrowers' risk of default payments manually, but this process is tedious and time consuming, which are not widely applicable concerns for online P2P platforms. This paper proposes a hybrid of the Simulated Annealing and the Extreme Gradient Boosting Machine models in order to predict the likelihood of default payments based on users' finance histories. Based on the experimental results, the proposed model demonstrates its predictability with high recall scores. The proposed model not only out-performs over conventional algorithms including Logistic Regressions, Support Vector Machines, Random Forests, and Artificial Neural Networks, but it also provides an efficient method for optimizing hyper-parameters in the machine learning algorithms. Through the utilization of the proposed data-driven models, the necessity of tedious and potentially inaccurate human labor can be significantly reduced, and service level agreements (SLAs) can be further improved by time reduction made possible through the introduction of advanced data mining approaches.
Keywords: Big Data; Data Mining; Extreme Gradient Boosting Machines; Credit Risk; Credit Scoring; Simulated Annealing.
Agile Polymorphic Software-Defined Fog Computing Platform for Mobile Wireless Controllers and Sensors
by Haymanot Gebre-Amlak, Abdoh Jabbari, Yu Chen, Baek-Young Choi, Chin-Tser Huang, Sejun Song
Abstract: Softwarization approaches in networks, storage systems, and smart devices aim to optimize costs and processes and bring new infrastructure definitions and functional values. A recent integration of wireless and mobile cyber-physical systems, with dramatically growing smart sensors, enable new types of pervasive smart and mobile urban surveillance infrastructures that open up new opportunities for boosting the accuracy, efficiency, and productivity of uninterrupted target tracking and situational awareness.Wireless sensors provide the tool for communications and security applications. They offer low-power, multi-functioning and computational capabilities.
In this paper, we present a design and prototype of an efficient and effective fog system using light-weight agile software-defined control for mobile wireless nodes. Fog Computing or edge computing, a recently proposed extension and complement for cloud computing, enables computing at the network edge in a smart device without outsourcing jobs to a remote cloud. We investigate an effective softwarization approach in the Fog environment for dynamic big data driven, real-time urban surveillance tasks of uninterrupted target tracking. We address key technical challenges of node mobility to improve the system awareness. We built a preliminary proof-of-concept Light-weight controller architecture on both Android- and Linux-based smart devices and tested various collaborative scenarios among the mobile nodes.
Keywords: Software-Defined Network (SDN); Internet of Things (IoT); Fog Computing; Cloud Computing; Wireless Sensors; Network Softwarization.
Outlier Detection Techniques for Big Data Streams: Focus on Cyber Security
by Fatima-Zahra Benjelloun, Ayoub AIT LAHCEN, Samir Belfkih
Abstract: In recent years, detecting outliers in Big Data streams has become a main challenge in several domains (i.e., medical monitoring, government security, information security, natural disasters, and online ﬁnancial frauds). In fact, unlike regular static data, streams raise many issues like high multidimensionality, dynamic data distribution, unpredictable relationships, data sequences, uncertainty and transiency. Most of the proposed approaches can handle some of these issues but not all. In addition, they provide limited considerations with regard to scalability and performance. Real-world applications require high performance, resources optimization and real-time responsiveness when detecting outliers. This is useful to extract knowledge, detect incidents and predict patterns changes. In this paper, we review and compare recent studies in detecting outliers for streaming. We investigate how researchers improved the outcome of different models and monitoring systems, especially in the context of cyber security.
Keywords: Outlier Detection; Data Streams; Streaming; Big Data; High Dimension; Cyber Security.
Improving Cloud Computing Services Indexing based on BCloud-Tree with Users Preferences
by Ahmed Khalid Yassine SETTOUTI, Fedoua DIDI, Mohammed HADDAD
Abstract: Wireless Sensor Networks and Cloud Computing are different but complementary. In a hand, the wireless nodes are resources limited and battery constrained. In the other hand, Cloud computing is unlimited in terms of computing, storage, network and power resources. Integrating such different concepts results obviously some troubles; especially for WSN owners who want to pick up the most suitable Cloud Computing provider. In addition, we suppose that both of the clients (WSN owners) and services are heterogeneous, various and dissimilar. In this paper, we propose an indexation method of public IaaS virtual machines in an AVL-Tree. For that, we employ a Z-order function to arrange services in the structure and make the research more efficient. Experiments prove the performance superiority of the proposed approach in comparison with similar works in the literature.
Keywords: Cloud Computing; Service Selection; User Preference; Quality Measure; Public IaaS; Wireless Sensor Networks; Service Ranking; Indexing; BCloud-tree.
Autonomic Resource Management Framework for Virtualised Environments
by Raman Bane, Annappa B.
Abstract: Virtualisation enables multiples virtual machines (VMs) to co-locate
on a same physical machine with total isolation. Hence using VMs to launch
web services or applications is the common trend nowadays in enterprise
information technology (IT). Data centre provides infrastructure to create,
configure and manage VMs. It has seen as a utility that clients can pay for only
as needed. The growing complexity of modern networked computer systems
with virtualisation technology necessitates the needs efficient resource
management. We have proposed an intelligent resource manager to control the
resource allocation in Xen virtualised environment for dynamically allocating
resources to individual VM. Our resource management architecture comprises
of fuzzy logic based controller. Experimental results shows that with the
proposed system data centre can efficiently allocate CPU resources to VMs that
have been produced by customers. The scaling of CPU resources is
automatically done in accordance with dynamically changing workload at a
minimum granularity of 2 seconds. It improves the resource utilisation by 30%
as compared to the ideal method while maintaining throughput as equivalent to
the ideal workload allocation.
Keywords: autonomic computing; resource management; virtualisation; fuzzy
logic; Kalman filter; service level agreement; SLA.
Special Issue on: High-Performance Computing Technologies and Emerging Services for IoT Systems
Energy-efficient Adaptive Distributed Data Collection method for Periodic Sensor Networks
by Ali Kadhum IDREES, Ali Al-Qurabat
Abstract: This article suggests a method, called energy-efficient adaptive
distributed data collection method (EADiDaC), which collects periodically
sensor readings and prolong the lifetime of a periodic sensor network (PSN).
The lifetime of EADiDaC method is divided into cycles. Each cycle is
composed of four stages. First, data collection. Second, dimensionality
reduction using adaptive piecewise constant approximation (APCA) technique.
Third, frequency reduction using symbolic aggregate approximation (SAX)
approach. Fourth, sampling rate adaptation based dynamic time warping
(DTW) similarity. EADiDaC allows each sensor to remove the redundant
collected data and adapts its sampling rate in accordance with the monitored
environment conditions. The simulation experiments on real sensor data by
applying OMNeT++ simulator explains the effectiveness of the EADiDaC
method in comparison with two other existing methods.
Keywords: periodic sensor networks; PSNs; data collection; adaptive sampling
rate; adaptive piecewise constant approximation; APCA; dynamic time
warping; DTW similarity; symbolic aggregate approximation; SAX; network
A Review of Testing Cloud Security
by Eric Zenker, Maryam Shahpasand
Abstract: The cloud computing paradigm is a nascent technology with many benefits for organisations. The adoption process is constantly advancing as the global revenue for SaaS increased by 14.8% in 2016. On the other side, security of clouds is still one of the major concerns of clients to adopt and use the new computing paradigm. The security of cloud environment underlies three key IT principles: availability, integrity and confidentiality. Likely attacks to cause security breaches are, for example, SQL injections or DoS attacks. One of the most important and effective security measures are encryption and authentication/authorisation to prevent such occurrences. To ensure a high level of security of cloud services and applications, testing is an appropriate approach to detect possible vulnerabilities before real case scenarios occur. In terms of clouds, testing is distinguished in TaaS and testing the cloud. Thus, many academic papers have been published to identify and address challenges in cloud security, vulnerabilities and threats. However, most of the researchers focused on TaaS rather than on testing the cloud, which led to a current gap in academics. This paper presents a systematic literature review of testing cloud security. The authors elucidate a general and consistent topic overview, beginning with defining and introducing key terms. Furthermore, gaps in recent related publications are revealed, hence prospective research implications are pointed out. This survey addresses challenges, vulnerabilities and threats regarding cloud security to foster the understanding and relations of current research fields.
Keywords: Cloud Computing; SaaS; Security; Testing as a Service; Threat; Vulnerability.
Rearranging links: A Cost-Effective Approach to Improve the Reliability of Multistage Interconnection Networks
by Fathollah Bistouni, Mohsen Jahanshahi
Abstract: One of the main ways to achieve a high computational power is the use of multiprocessor systems. Multistage interconnection networks (MINs) are widely used in parallel multiprocessor systems to connect processors and memory modules. Therefore, design of an efficient MIN is very critical for the construction of high performance multiprocessor systems. On the other hand, reliability is one of the most important performance parameters in the context of interconnection networks. However, hardware cost is a limitation in the design of high-reliable interconnection networks. In this paper, a new approach to improve the reliability of the MINs, called the rearranging links is proposed. The proposed approach is implemented on two common MINs namely extra-stage shuffle-exchange network (SEN+) and augmented shuffle-exchange network (ASEN). Meticulous analysis of terminal reliability proves that the proposed approach is an efficient method to improve the reliability of MINs. In addition, performed cost analysis confirms that utilizing it leads to emerge cost-effective MINs.
Keywords: Multiprocessor systems; Multistage interconnection network; Reliability; Cost-effectiveness; Reliability block diagrams.
Distributed algorithm to fight the state explosion problem
by Lamia Allal, Ghalem Belalem, Dhaussy Philippe, Ciprian Teodorov
Abstract: Model checking, introduced 20 years ago, combines several fully automatic techniques in which the property to be checked is tested exhaustively on all the possible executions of the system. It is an automated approach to verifying that a system meets its specifications. The main limit to the use of model checking is related to the state explosion problem, which occurs when the number of states increases exponentially according to the complexity of the system. In this Article, we presented a distributed exploration algorithm executed on two different architectures to fight this problem. The first one is using 2 real machines interconnected across the network and the second using 2 virtual machines in a cloud computing. We carried out a comparative study between these two distributed approaches as well as a parallel approach studied in Allal et al. (2016). The aim of this paper is to give the advantages and drawbacks of each solution.
Keywords: Model checking; state explosion problem; parallel exploration; distributed exploration; execution time; memory space.
Voice Over IP on Windows IoT Core
by Maryam Shahpasand, Ramlan Mahmod, Nur Izura Udzir
Abstract: Tremendous growth of Internet of Thing integrated with VoIP applications give a serious challenge to digital forensic researchers. This integration gives more challenges in investigation process because there are various types of VoIP application with different design and implementation features. There are diverse VoIP applications used by criminal that caused difficulties in the identification, acquisition, and preservation of evidential data. This paper used Skype to determine the data remnants on Windows 7 and Windows 8.1 when users run Skype functions including installing and uninstalling, instant messaging, voice and video call, video messaging, sending and receiving files, screen sharing and taking pictures. The link where the victim and suspect may have been in contact on Skype is provable by the proposed methods. It is found that potential evidences can be found in capturing memory, capturing network traffic, user application data and the data remnants available in users device.
Keywords: Voice over IP; Digital Forensics; VoIP Application; Skype; Application investigation; Internet of Thing (IoT).
Fuzzy Based Dynamic Packet Priority Determination and Queue Management method For Wireless Sensor Network
by Maya Shelke, Akshay Malhotra, Parikshit Mahalle
Abstract: Wireless Sensor Networks are made up of large number of
resource-constrained sensor nodes. Scheduling of different types of packets at
sensor nodes is of crucial importance to reduce sensors energy consumption,
end-to-end data transmission delays and packet loss. Majority of the existing
packet scheduling algorithms such as first come first serve (FCFS), preemptive
priority scheduling and non-preemptive priority scheduling are not adaptive to
changes in the data traffic. They also have more processing overhead and large
communication delays. We propose fuzzy-based dynamic packet priority
determination and queue management mechanism. In the proposed scheme,
each node determines priority of packets dynamically and queues them
accordingly. The proposed scheme increases fairness in scheduling and the
energy efficiency by delivering the packets before their expiry. The results
demonstrate that this enhanced approach outperforms FCFS and dynamic
multilevel priority queue scheduling algorithms in terms of throughput, end-toend
delay and average residual energy.
Keywords: wireless sensor networks; WSNs; fuzzy logic; packet priority;
packet scheduling; first come first serve; FCFS; preemptive priority scheduling;
non-preemptive priority scheduling; data waiting time; end-to-end delay;
An improved prediction based strategy for target tracking in wireless sensor networks
by Hanen Ahmadi, Ridha Bouallegue, Federico Viani, Andrea Massa
Abstract: The indoor localization of moving target in Wireless Sensor Networks using Received Signal Strength Indicator (RSSI) is addressed in this paper. A novel location tracking algorithm which combines an ensemble learning method and Kalman filter is proposed. An ensemble based regression tree using received signal strength method has been proposed to localize static sensor nodes. In this paper, this approach is employed to solve the complex relation between the RSSI behavior and the target position. Then, the estimated location is introduced in the Kalman Filter as the observed information, leading to more accurate state of the moving target. Experimental results show that the adopted solution achieves a high accuracy compared to localization algorithms currently available in the literature.
Keywords: target tracking; localization; wsn; machine learning; kalman filter.
QoS Oriented and Delay Tolerant WSN Routing Protocol for Data Gathering in IoT Ecosystem
by Shivkumar S. Jawaligi
Abstract: In this paper, a robust and efficient delay tolerant and quality of
service (QoS) oriented data gathering protocol for low power lossy wireless
sensor network (WSN) has been proposed. Our proposed routing protocol
applied received signal strength based forwarding node selection and
transmission path formation scheme, which has been further armoured with
multiple timer based handoff optimisation to enable optimal data transmission,
particularly data gathering using single mobile sink node. To ensure backward
compatibility of RPL, our proposed scheme has incorporated control message
modification that makes our proposed routing protocol applicable for major low
power lossy network commonly known as RPL based internet of things (IoT)
ecosystem. The higher packet delivery ratio of 98.93% and lower delay and
control packet requirements make our proposed routing protocol
computationally efficient to be used for major WSN based IoT communication
Keywords: data gathering in WSN; single mobile sink node; radio signal strength indication; RSSI; best route selection; RP: IoT.
Special Issue on: Security, Privacy and Trust in Computing and Secured Transactions
Dynamic High Bandwidth (DHB) Nodes for Routing in MANETs
by Jayalakshmi Periyasamy, Saravanan R
Abstract: High bandwidth routing is the most desired advantage in networks with portable nodes. The main objective of this work is to obtain a high bandwidth route for increasing the delivery rate in MANETs. Dynamic high bandwidth (DHB) nodes are picked for data transmission in MANETs. A measure from the current packets received by a node and the packet delay and the bandwidth are used to calculate the total transmission efficiency of a node. Thereby the routes are identified by this dynamic estimation to improve routing capability in MANETS. Analysis of the performance of the protocol is carried out by using the network simulator (NS-2).
Keywords: Routing; bandwidth; mobile ad hoc networks; performance analysis.
A Novel Dyadic Multiresolution Wavelet Image Steganography using N-ary
by Chandrasekaran Vanmathi, S. Prabu
Abstract: Steganography plays an important role in information sharing. In this paper a wavelet based image steganography using Haar wavelet and an N-ary notation is proposed. The high and middle frequency coefficients are selected based on the Shannon entropy value to identify the best sub band for data hiding. Peak signal to noise ratio and Structure similarity index metric values are computed from the stego image. The empirical results show the proposed method provides good, better imperceptibility and data capacity with average Peak Signal to Noise Ratio of 53.60 dB for 359,112 bits in terms of effectiveness. To prove this accomplishment of the method, several experiments were conducted and compared the results with existing works.
Keywords: Steganography;Haar; IWT; Nary.
Event Detection in Sports Video based on Audio- Visual and support vector machine. Case-Study: Foot Ball
by VIJAYAN ELLAPPAN, RAJKUMAR R
Abstract: In this paper we propose a novel audio-visual feature-based framework, for event detection in field sports broadcast video. The system is evaluated via a case-study involving MPEG encoded football video. Specifically, the features gathered by various feature detectors is combined by means of a support vector machine, which infers the occurrence of an event, based on a model generated during a training phase, utilizing a corpus of 2.5 hours of content. The system is evaluated using 2.5 hours of separate test content.
Keywords: Event Detection; Field sports video; MPEG; Support vector machine.
Risk - based availability modelling and reputation management on fault tolerant cloud computing systems
by Deepa M, Anand Mahendran
Abstract: This paper exhibits a risk-based philosophy in cloud computing to estimate ideal quality and maintenance which maximise the high availability of cloud administration infrastructure. The procedure is confined into two stages: 1. accessibility displaying the cloud frameworks, 2. Hazard based assessment and maintenance estimations. The technique is easy but difficult to apply and needs promptly accessible information in a cloud environment. The approach can be further improved by comparing the existing inspections with the previous consequences of reviews. The projected procedure is practical to the health care scheme using Markov chain process. The proposed system predicts, mitigate and eliminate the risk-based inspection and Markov chain process to efficiently identify the repair and failures of each virtual machine and reduce the energy consumption rate, cost accordingly. The result of our proposed method will definitely bound optimum solutions and specifies the conquest of an efficient risk-based availability modelling on minimal cost and energy consumption. It is developing as a dynamic innovation to modernise and rebuild health care services association to give best administrations to the customers. Finally, the proposed model is verified by the Nagios and OPTIMIS toolkit. The result obtained in our proposed model definitely bounds optimum solutions and deceptively specifies the triumph of an efficient risk analysis of failures on minimal cost and energy consumption.
Keywords: Risk-based approach; Risk-based Inspection; Mitigation; Markov Process; Revenue; Energy consumption.
Cost Based Constrained Task Scheduling in Cloud Environment
by AR.ARUNA RANI, Dr.D.MANJULA
Abstract: In recent years the most important requirement in the cloud computing environment is the task scheduling which is the key role for efficiency in sharing of cloud resources among multiple users. Cloud provider is always assumed to own its large data centre which has significant computational resources with it. In the cloud environment all the tasks are allocated and executed by using the available services in order to achieve higher performance, least total time for computation, shortest period of response time and utilization of resources and so on. There are some serious challenges that the existing models could allocate the task to the resources without the profit maximization scheme. The main motivation that is behind this paper, is to design and to develop a CLOUD manager(CM) to efficiently manage the cloud resources and also completing the jobs for the allocated resources for the given task in the cloud environment. It is implemented using a prior resource optimization (PRO) based allocation algorithm that takes into account execution time, transmission time and cost. The desirable feature of this paper is that the resources are allocated as per the cloud consumer request. The potency of this is presented in the cloud environment by finding the optimal and suboptimal allocation scheme of resources which maximize the profit of cloud provider and also improve the quality of scheduling solution.
Keywords: Cloud Computing; Cloud Manager; Resources Scheduling.
An Efficient Spectrum Handoff Decision Making Scheme for Cognitive Radio Networks
by Preetha K S, Kalaivani S
Abstract: There has been a gigantic spike in the usage and development of wireless devices since the time wireless technology has come into existence. This has contributed to a very serious problem of spectrum unavailability or spectrum scarcity. The solution to this problem comes in the form of cognitive radio networks where the secondary user which is also known as the unlicensed users makes use of the spectrum in an opportunistic manner. The secondary user uses the spectrum in a manner such that the primary or the licensed user doesnt face interference above a threshold level of tolerance. Whenever a primary user comes back to reclaim its licensed channel, the secondary user using it needs to perform a spectrum handoff to another channel which is free of primary user. Our primary focus is on performing spectrum handoff decision making. The SU selects staying or changing policy based on the average extended delivery time. The spectrum handoff decision making is performed, i.e. the optimal channel for spectrum handoff is decided only if changing policy is adopted which is based on Multiple Attribute Decision Making (MADM). This spectrum handoff decision making scheme is later extended using Artificial Neural Networks (ANN) and probabilistic Markov Model.
Keywords: secondary user; spectrum handoff; Cognitive radio Networks; Multiple Attribute Decision Making (MADM),Artificial Neural Networks (ANN) and Markov Model,.
Enhancing Network Lifetime through Power-aware Routing in MANET
by Rakesh Kumar S, Gayathri N, Balamurugan Balusamy
Abstract: Mobile Ad hoc Network (MANET) is a self-organized network that allows communication between the nodes that are in radio range of each other. MANET nodes can join and leave the network dynamically, leading to a rapid change in network topology. As not all nodes in MANET are in radio range of each other, the intermediate nodes help in routing of the packets. The packets are transferred from the source node to the destination node over the network. As the nodes in MANET are battery powered, the intermediate nodes may at times lose its power completely which might lead to partitioning of the network. Hence, the communication between the nodes might get disconnected and thus the lifetime of the network gets reduced. Thus, the limited power resource is one of the major disadvantages here, as the batteries cannot be recharged or replaced in many of the locations where MANETs are deployed. This work is aimed at providing a solution mechanism that efficiently utilizes the existing power resources in MANET nodes thereby extending the lifetime of the network.
Keywords: MANET; Routing Protocol; Power-Aware routing.
Privacy Preserving Computation of Scalar Product and Sign of Scalar Product
by Subrata Bose
Abstract: Scalar product is repeatedly used in a large family of applications. It is a useful building block of many scientific and business applications. Secure scalar product computation is widely used in many privacy-preserving computation domains. In this work, we have proposed privacy preserving protocols for computing scalar product or only its sign. These protocols work on two basic principles random data perturbation and algebraic methods, and thus avoid standard encryption/decryption overheads. We have designed the protocols to get sign of the scalar product, which can act as a basic building block in privacy preserving database queries over distributed databases and many other applications. We have developed two sets of protocols for the two-party computation with and without using an untrusted third-party. Experimental results on generated random datasets show that the proposed protocols indeed involve low communication overhead.
Keywords: secure multi-party computation; two-party protocol; privacy preserving database query processing; privacy preserving data mining.
SECURE COMMUNICATION PROCESS IN IoT USING MEDIA GATE NETWORK TRANSMIT PROTOCOL WITH RELIABLE DATA TRANSPORT PROTOCOL
by Premalatha T, Duraisamy S
Abstract: Internet of thing (IoT) is the important concept for making the effective and secure communication between the networks. During the communication process the security and intermediate attack is one of the main issues because the communication may be used in the various applications such as energy management, infrastructure analysis and environmental monitoring process so on. This issue has been overcome by applying the effective transmission protocol along with the secure encryption method. Initially, communication process is enhanced and making reliable with the help of the Media Gate Network Transmit protocol along with the reliable data transport protocol. In addition, the intermediate attacks present in the network communication process have been resolved by using the fuzzy soft multi-set blowfish encryption method. The application layer transmission protocol with the encryption method ensures the secured communication when compared to the other protocol based communication. Then the efficiency of the system is evaluated with the help of the experimental results in terms of the energy consumption and throughput metrics.
Keywords: Internet of Things (IoT); Media Gate Network Transmit protocol along with the reliable data transport protocol; fuzzy soft multi-set blowfish encryption; energy consumption and throughput metrics.
Performance Analysis of Cloud Computing Using Series of Queues with Erlang Service
by K. Santhi, R. Saravanan
Abstract: In this paper, we have proposed a priority based service distribution method using Erlang distribution with k - phases for cloud computing architecture. The multiple users from the public cloud entering into two serially connected M/M/s and M/Ek/1 (Erlang Service Queue) queues are served naturally based on the non-pre-emptive priority discipline. We have assumed that each user of different priority class i, (i ≥ 2) desired to wait until the current user is being served if priority of the service is similar, as per the first come first service policy. If the servers are free, users can enter into the M/M/s queue, then enter into the M/Ek/1 queue with probability ϕ and leave the system after service completion or leave the system with probability (1- ϕ) without entering into the ESQ. Our proposed work is based on request from the public cloud, resource management application and the performance is analysed in terms of waiting time defined as Quality of Service (QoS). We have obtained waiting time for both the queues and the total waiting time of different class i of units in the cloud system. Finally, the numerical results obtained in our proposed model are considerably reducing the total waiting time of different class i of units in the cloud system than the existing model and more utilization of service in cloud.
Keywords: M/M/s queue; Erlang service queue; Non-pre-emptive; cloud computing; Quality of Service; Waiting time.
Spatial Data Storage and Retrieval in Cloud Computing Environments using Attribute based Encryption Algorithm
by Prabu Sevagan, Karthi S
Abstract: Cloud computing consists of the hardware, software systems, and programs which added as services over the network. It offers the get entry to the device for using resources anywhere and anytime with usage-based pricing, rapid resource elasticity, transference of risk, place unbiased useful resource pooling and so forth. Most cloud carrier vendors provide services at a vast degree that have price lists for the kind of the elastic storage, elastic computing, or the elastic bandwidth. The information is stored in cloud service issuers devices on multiple machines throughout the whole virtual framework. The records are also accommodated on devices that belong to infrastructure provider. The cloud service company wishes to ensure customers that the security in their facts is being appropriately addressed between the partners, that their digital environments are isolated with sufficient protection, and that the cleanup of outdated data is being definitely controlled at cloud infrastructure providers storage machines. In this paper, we are able to store and retrieve the spatial facts in cloud storage in a relaxed manner. Security in spatial facts is undertaken by way of the attribute based encryption algorithms which affords efficient encryption of spatial data. In our cryptosystem, put into consequence of multi authority attribute based encryption (MA-ABE) that involves of cryptograph texts are categorized based on attributes and personal secrets are related to getting admission to systems that manage cipher texts of a consumer is capable to decrypt. This method effectively secures the statistics and additionally gives the correctness of the retrieved facts alongside the recovery mechanism for the transmitted data in case of malicious assault. The implementation of this scheme will display the correctness of the cozy facts garage and the recuperation method
Keywords: Spatial Data; Cloud computing; Cryptosystem; Cipher texts; Multi authority; Data correctness.
Efficient Authentication and Key Management Scheme for Wireless Mesh Networks
by Amit Roy, Ajoy Khan
Abstract: Abstract: Wireless Mesh Network(WMNs) is considered as one of most emergingrnfield for the research work in todays networking area due to its variousrnapproaches available to handle the network resources. Various architecturesrnhave been proposed so far and main key challenge for the design of thisrnnetwork is their vulnerability to security attacks. The growing popularity of WMNs are directly proportionate to their propensity for security exploitation. Due to their growing size, WMNs needs to be clustered into multiple groups to achieve fast and efficient security mechanism to overcome from security attacks. Therefore, we have proposed a Group Key Agreement protocol based on Diffie-Hellman key agreement protocol and embedded Digital Signature to authenticate the members within the group. Our protocol is resistant against, repudiation attack, confidentiality and integrity attack with efficient communication and computational cost which results in the great degradation of packet loss by an attacker throughout the WMNs.
Keywords: Wireless Mesh Networks; Authentication; Clustering; Key Management; Diffie-Hellman; Digital Signature; Security Attacks.
Special Issue on: Wireless Networks and the Internet of Things
TRAM Based VM Handover with Dynamic Scheduling for Improved QoS of Cloud Environment
by Nadesh R.K, Aramudhan M
Abstract: The generic view of cloud has seen changes with the entry of cloudlet which combines the servers located in any local area network that can be accessed through any wireless communication. Modern cloud computing has opened avenues for resource and service providers for deployment of their resources irrespective of location. The only issue is the choice of the relevant service provider for the cloud client. There are a number of scheduling algorithms discussed earlier. Resources have been grouped on the basis of various constraints. Yet the methods are unable to achieve the required quality of service parameters. With a view to overcome the issue of previous methods, an efficient TRAM (Throughput-Resource Availability-Makespan) based clustering, VM Handover, with Scheduling is discussed in this paper. The TRAM based approach maintains a list of requests processed on each moment by different cloudlets and groups of the cloudlets according to the TRAM measure. The same TRAM measure is used for making decisions on the handover and scheduling of the request based on TRAM. The recommended approach produces auspicious results on the various qualities of service parameters and produces satisfactory results.
Keywords: Cloud Computing; Cloudlet; VM Handover; Clustering; Scheduling; TRAM.
Improved Scrum Method through Staging Priority and Cyclomatic Complexity to enhance Software Process and Quality.
by Vijayanand Rajasekaran, Dinakaran Muruganandam
Abstract: Software Development has been inevitable in the modern era. In olden days, organizations followed intense traditional software process; but currently, the focus has turned greatly towards agile methodologies. In agile methodology, Scrum is the mostly followed process. But it comes with a bunch of technical and generic issues. For instance, Assigning, prioritizing and integrating product backlog items prove to be difficult to deal with in agile methodology. On the other hand, it poses several other generic issues ranging from environment problems due to idle team participants and Developer-Tester issues. In this paper mainly concentrates on overcoming the technical issues mentioned above with the assistance of a framework which is perfectly refined in addition to the introduction of a new term called RScrum which is the extension of Scrum which will greatly help to overcome the glitches
Keywords: Agile; Scrum; Staging Priority; Cyclomatic Complexity; Product Backlog Item; sprint;.
Intelligent Intrusion Detection System Using Temporal Analysis and Type-2 Fuzzy Neural Classification
by Rama Prabha Krishnamoorthy Pakkirisamy, Jeyanthi N
Abstract: Cyber-attack detection is an important and challenging area of research inthe field of information technology. In such a scenario, intruders introduce new mechanisms by applying polymorphic mechanisms in order to escape from the intrusion detection systems. This leads to loss in data and increase in security vulnerabilities. In the past, many soft computingtechniques were used from the field of machine learningfor enhancing the efficiency of intrusion detection systems (IDSs) in computer networks. Among them, fuzzy logic playeda major role for making effective decisions. In addition, the neural networks are also contributing more in this area for training the datasets to form rules which can be used to develop an effective intrusion detection system. In this paper, we propose a new intrusion detection system by combining neural networks with temporal and type-2 fuzzy logic for performing effective classification of the dataset. In addition, a new feature selection algorithm is also proposed in this paper which uses information gain of attributes with fuzzy logic decision making for selecting the optimal number of features from the dataset. This work has been tested by using NSL-KDD dataset and through the experiments conducted in this work it is proved that the proposed system increases the intrusion detection accuracy and reduces the false positive rate when it is compared with other existing systems.
Keywords: Neural Networks; Type-2 Fuzzy Logic; Intrusion detection System; NSL-KDD dataset; Feature Selection; Classification.
Wireless Camera Network with enhanced SIFT Algorithm for Human Tracking Mechanism
by Ushadevi G, Priyan M K, Gokulnath C
Abstract: In order to deal with the Wireless Camera Networks (WCN), whose detectingrnpower of conventional camera networks with elasticity, re configurability and with an simple deployment of Wireless Sensor Networks (WSN) for efficiently addressing the significant responsibilities in the method of cluster based human (object) tracking, such as integrating the measurement, including or ruling out in the cluster and cluster head rotation. The WCN effectively uses division friendly representation and methods in which every node contributesrnto the estimation in each methodology without the requirement of any previous information of the remaining the nodes. These methods are integrated in two different schema so that they can be deployed with the same mean time without considering the cluster size. Thus, the observation and practical evaluation shows that the proposed schemes and methodology drastically reduces the energy consumption and computational trouble in accordance to the existing methodology.
Keywords: cluster; human frames; sensors; SIFT.
BMAQR: Balanced Multi Attribute QoS Aware Replication in HDFS
by Kumar PJ, Ilango P
Abstract: The Hadoop Distributed File system (HDFS) replicates data to ensure data availability in case of a failure caused by events such as data node crash, disk failure, switch/rack failure or corruption in the data block. The evolution of big data leads to large population of data stored and managed in the clusters of cloud. The degree of replication is directly proportional to availability of data with an increase in the replication cost and update cost of data blocks in cloud. The applications executed on the data nodes demand various QoS needs while a block of its data is replicated such as disk access latency, constant bandwidth, delay, jitter etc. Existing replication algorithms replicates data based on the replication factor and the specified QoS needs of application. At a given point of time we expect the types of replication request from different applications varies largely and there is a need to allocate replica based on the request type and the replication factor to achieve a balanced replication cost and availability of data with the available block spaces in the entire cluster. We propose a multi attribute QoS replica allocation algorithm to replicate data considering the different types of replica request, replication factor and the total available space to achieve a balanced replica allocation. The proposed algorithm satisfies different QoS needs of applications and reduces the number of QoS violated replicas when the request consists of different QoS types. We measure the performance of the proposed algorithm in allocating replica and the reduction in number of QoS violated replica count over the existing algorithms such as Random replication. The simulation result shows a better performance over the existing algorithms with a slightly increase in the computational time.
Keywords: HDFS; Replication; Multi Attribute QoS aware replica allocation; QoS Violation.
Generating Various Kolam Patterns using New Kolam Picture Grammar
by Ramya Govindaraj, Anand Mm
Abstract: Kolam is an artistic creation .It is a ubiquitous art form predominant in South India, while also seen in a few places in northern India and South East Asia.Kolam holds a rich tradition of cultural and medicinal significance. Kolams are generated using kolam grammar. This paper consists of set of rules which is used for manipulating kolam patterns under defined rules using axiom. It is enclosed under defined alphabets used for creating kolam patterns.We can generate many kolams with n number of pullis(dots) with finite number of rules.
Keywords: Formal theory;Picture languages;Kolam pattern;Kolam grammar ;kolam picture language.
Hilbert Fast-SAMP with Different Channel Estimation Schemes of BER Analysis in MIMO-OFDM system
by Kumutha Duraiswamy, Amutha Prabha N
Abstract: In the OFDM system, there are huge number of sub carrier and high range of signal that produce a very high peak to average ratio reduction (PAPR), so that the signal degrades and further effects the overall Bit Error Rate (BER) performance. The channel estimation techniques are used to avoid much training overhead, that makes an issue in coherent detection. Sparsity Adaptive Matching Pursuit (SAMP) is an existing, thereby the backward pursuit iteration can be repeated for many times, if the support set expands. Due to this iteration, the performance of BER increases, delay occurs and also provides computationally complexity. To avoid the backward pursuit iteration, Hibert-fast sparsity adaptive matching pursuit (HF-SAMP) is proposed which reduces the computational complexity and decreases the BER performance to the maximum extent. Zero padding is also appended, results in better improvement of BER performance. The performance of BER, SNR, MSE and PAPR using the Channel Estimation (CE) and Pilot Design (PD) techniques are analyzed and the proposed technique yields better and thereby performance rate increases than the other existing conventional algorithms. MATLAB is used for performing the simulations.
Keywords: CE; HF-SAMP; OFDM; BER; PAPR; Pilot Estimation; ZP and SOMP.
Impact of wave frequency in Underwater Wireless Sensor Network route Discovery
by Anuradha Vanu
Abstract: Improvement in communication technologies have initiated a remarkable revolution across the globe and even across planets. Although Terrestrial communication has reached an advanced level, underwater communication is only in its infancy. The factors that affect underwater communication are signal propagation in multiple paths, time variations of the channel, low bandwidth and signal attenuation when transmitting to longer distances. Usage of low frequency waves have resulted in a comparatively low data transmission rate in underwater communication. The commonly used waves are acoustic, electromagnetic and optical waves. The wavelength of these waves are different and so data transmission rate also automatically varies. This paper describes the impact that the frequency of transmission waves have on Route discovery in Underwater Wireless Sensor Networks.
Keywords: Wave frequency; UWSN; Route discovery; Routing; Acoustic.