International Journal of Internet Protocol Technology (37 papers in press)
Iterative Learning Feedback Control of Network Inverse System
by Xuelian Yang
Abstract: The traditional iterative learning feedback control has the problems of large feedback error and long searching time. Based on instruction set operation, the hardware part constructs the administrator module, the teacher module and the student module, and carries on the detailed analysis. In the software design of the system, based on the system dynamics method and genetic algorithm, an iterative learning feedback controller for the network inverse system is proposed, which can effectively improve the anti-interference performance of the system. The experimental results show that the feedback error of the designed system is less than 1% and the searching time of learning materials is less than 200 ms, which proves the practicability of the designed system and lays a theoretical foundation for the further development of iterative learning feedback control of network inverse system.
Keywords: Modular teaching; Network inverse system; Iterative learning; Feedback control system.
The Quality Factor for detecting Node Isolation Attack in Mobile Ad hoc Networks Using OLSR Protocol
by Abdellah NABOU, My Driss LAANAOUI, Mohammed OUZZIF
Abstract: The Optimized Link State Routing (OLSR) protocol is a proactive routing protocol for Mobile Ad hoc Network (MANET), it is more suitable for large and dense mobile networks thanks to its new concept of Multi-Point Relay (MPR) nodes that reduce the overhead of the network, unfortunately the performance of OLSR routing protocol can be affected by various routing attacks. Node Isolation Attack is considered as a DOS (Denial of Service) attack that affects the function of OLSR routing protocols precisely by isolating the victim nodes and hiding them from the network. In this paper, we propose a new method to detect the Node Isolation Attack by using a modified version of the Quality Factor (Q) that is applied in the physical domain in order to calculate the Q of OLSR control messages and detect the attack. The experimental results show that when the attack is launched in the network between 30 and 70 second, our method can detect it without any modification in the algorithm of OLSR protocol.
Keywords: MANET; Node; Security; OLSR; MPR; Quality Factor; Node Isolation Attack.
Advance Routing Strategy for VANETs
by Amrit Suman, Chiranjeev Kumar, Preetam Suman
Abstract: The VANET is an autonomous kind of network in which the nodes can create a wireless connection without the control of base stations. In recent years VANET has become a massive point of attraction for researchers because of its unique characteristics that are link failure and frequent changes in topology because of its high mobility. This makes VANET unique from the mobile ad-hoc network. Intelligent transportation that is a part of VANET helps in increasing transportation efficiency, enhancing safety in traffic and, improving the driving experience. Apart from these benefits, Network instability is the main drawback of VANET that reduces network efficiency. Due to various reasons, a high range of security measures required from multiple network attacks to protecting the communication between the vehicular nodes. In this paper, a routing strategy is proposed, which is based on AODV and MAC to enhance the route discovery and to avoid the collision. The proposed routing strategy consists of automatic size adjustment of contention window depending on the network capacity, channel allocation for each node, priority assigning for different types of messages, and security checking for each packet using CRC; all these are based on MAC. Route discovery and table preparation are based on the AODV. The proposed routing protocol (P-Routing) has been implemented in Qualnet 5.0. The results with the performance of C-AODV then compared. The parameters taken for comparison is total byte received, the signal received with error, total packet loss, and throughput. The number of nodes and speeds of nodes kept in variation to create different scenarios. In all cases, the performance of the proposed protocol is better. The results are described with the graphs in the result section.
Keywords: MAC; AODV; Contention window; Message priority; Network Attacks; Collision avoidance; Channel Allocation.
Position-related Content Acquisition for CCM
by Yanli Li, Xiaonan Wang
Abstract: The content-centric networking (CCN) depends on reverse paths and limited broadcast to achieve content acquisition, but the reverse-path disruption due to node mobility leads to content acquisition failures and flooding results in considerable content acquisition costs. In this paper, we propose a Unicast-based content acquisition scheme for Content-Centric MANET (UCCM) to reduce content acquisition costs and improve success rates. UCCM employs the address-centric unicast instead of the content-centric broadcast to achieve the content acquisition, so the content acquisition cost is lowered. Moreover, a requester acquires the content from the nearest provider in the address-centric unicast way, so the content is returned to a requester based on the requesters address rather than the reverse paths. UCCM is evaluated, and the analysis results show that UCCM reduces the content acquisition cost by nearly 63.8% and improve the success rate by nearly 5.9%.
Keywords: Content-centric; address-centric; unicast; broadcast.
Construction of Emergency Dispatching and Controlling Platform for Multi-elevator in Cloud Computing
by Junjun Liu, Jian Wu, Lanzhong Guo
Abstract: Traditional elevator emergency dispatching platforms are limited by their computing power, they cannot automatically collect knowledge and learning information, and they can easily fall into local optimization problems. Therefore, in the context of cloud computing, a multi-elevator emergency dispatching control platform is constructed through fuzzy control technology. According to the fuzzy control input amount, the weighting coefficients of waiting time, driving time and the congestion degree of the cabinet are continuously updated to obtain the optimal weighting coefficient. The maximum membership degree method is used to perform the deblurring processing, and the maximum value in the fuzzy output vector is used as the data after the deblurring processing to obtain the emergency dispatching result of multiple elevators. The results show that the average waiting time of the platform is 20.35s, less than other platform methods, which indicate that this platform has excellent dispatching performance and good application prospects.
Keywords: cloud computing background; multi-elevator; emergency dispatching; control platform; construction.
Study on Network Security Intrusion Target Detection Method in Big Data Environment
by Yingkai Miao, Jia Chen
Abstract: In view of the traditional network security intrusion target detection method can not effectively estimate the trend of the intrusion target, resulting in poor detection accuracy, a new network security intrusion target detection method under the big data environment is proposed. Set up under the environment of big data sequence model of network intrusion in the invasion of the information collected from different data center, according to the binary feature of syntax tree for the intrusion information decomposition, the invasion of the target and get the feature sequences, with closed frequent search method, combining with the characteristics of sequence invasion of target extraction, using path, trends of binary weighted semantic of intrusion path direction get trend path set, exception path is obtained by covariance correction model trend estimation results, achieve network security intrusion detection. The experimental results show that this method has a better performance and better stability in the estimation of intrusion target path trend, with an estimated accuracy of between 94.9% and 98.6% and a detection time of 0.24-0.38s.
Keywords: Big data; network security; intrusion target; path trend; detection.
Design of Hole Repair System for Wireless Sensor Networks based on Triangle Partition
by Zheng Xie, DaQin Wu, HaiYan Hu
Abstract: Aiming at the problems of low coverage, high redundancy and low repair efficiency in the current design methods of network hole repair system, a design method of wireless sensor network hole repair system based on triangular partition method is proposed. The location and shape of holes in the bottleneck area of wireless sensor networks are determined ; the best interior points of the hole edge in the bottleneck area are obtained, and the moving direction and distance of sensor nodes in wireless sensor networks are calculated; the best interior points are selected according to the results of calculation, and the holes in the bottleneck area of wireless sensor networks are self-repaired. The experimental results show that the coverage level of the proposed method is always higher than 80%, and the redundancy can be stabilized below 20%, laying a foundation for the further application of wireless sensor networks in practice.
Keywords: Triangular partition; Wireless sensor network; Bottleneck area; Hole repair.
Small Area Purification and Recognition of Network Intrusion Signals Based On the Second Order Matching Filter Detection
by Yucai Zhou, Lianguang Mo
Abstract: In order to improve the ability of intrusion detection and recognition. This paper proposes a method of small area purification and recognition of network intrusion signal based on second-order matched filter detection. In this method, the time-frequency analysis of network intrusion signal is carried out, and Hilbert Huang transform is used to decompose the time-delay scale of small-scale network intrusion signal, and then the spectrum feature is input into the second-order lattice matched filter to improve the signal resolution, and adaptive weighting method is used to adjust the filter tap coefficient to improve the detection and recognition ability. The simulation results show that the method can accurately recover two groups of component information of network intrusion signal: sinusoidal signal and sinusoidal frequency modulation signal. The recognition accuracy of network intrusion signal can reach 100%, which shows that the method has good signal purification performance.
Keywords: network intrusion signal; detection; filter; recognition; spectral characteristic quantity extraction; time-frequency analysis.
Risk Assessment Method for Power Grid Communication Link Failure Based On Fuzzy Comprehensive Assessment
by Liang Wei, Lianguang Mo
Abstract: In order to overcome the problems of long time and inaccurate evaluation results of traditional power grid communication link fault assessment methods, a new power grid communication link fault risk assessment algorithm based on fuzzy comprehensive evaluation is proposed. The fuzzy comprehensive evaluation method is used to comprehensively evaluate the risk of the power grid communication link. Based on the failure rate curve of the power grid failure rate model and the Weibull distribution function, a power grid communication link failure risk analysis model is established to complete the power grid communication link failure risk assessment. The experimental results show that compared with the existing risk assessment algorithms, the average assessment time is shortened by 17 seconds, the accuracy of the assessment results is increased by 7.9%, and the cost is reduced by 23.35%.
Keywords: Power grid; communication link; risk assessment; failure fault; fuzzy assessment.
Security Enhancement of an Auditing Scheme for Shared Cloud Data
by Reyhaneh Rabaninejad, Maryam Rajabzadeh
Abstract: In cloud storage services, public auditing mechanisms allow a third party to verify integrity of the outsourced data on behalf of data owners without the need to retrieve data from the cloud server. In some applications, the identity of data users should be kept private from the third party auditor. Oruta, is a privacy preserving public auditing scheme for shared data in the cloud which exploits ring signatures to protect the identity privacy. In this paper, we propose two attacks and demonstrate that the scheme is insecure and a dishonest server can arbitrarily tamper the outsourced data without being detected by the auditor. We also propose a solution to remedy this weakness with the minimum overhead and without losing any desirable features of the scheme. Performance evaluation demonstrate acceptable efficiency of improved scheme in comparison to the original protocol.
Keywords: Cloud storage; shared data; public auditing; security analysis.
Secure node ID assignment for Internet integrated sensor network
by Amit Kumar Gautam
Abstract: Internet integrating sensor network (IISN) has gained much importance and exponential growth has been seen over the last twenty years. It is typically installed in remote and unattended terrains to monitor, process and collect time-critical and sensitive data. Internet integrated wireless sensor network can be used in various critical sectors such as monitoring of nuclear power plant, disaster management, internet of things (IoT), industrial management etc. As the application area of sensor network is increasing rapidly, the adversaries can trigger duplicate ID based attacks such as Clone and Sybil attacks. In this paper, for joining a new node in the existing network, we propose a secure identity assignment who wish to join the network with the help of any existing node of the network. With the collaboration of an existing node, an overlay ID will be assigned to new node which is secured by using a public key cryptography. The paper included a complexity and communication overhead analysis to demonstrate the effectiveness of proposed method which maximizes the defence/protection against ID based attacks. Complexity analysis demonstrates the superiority of the proposed method.
Keywords: ID based attacks; public key cryptography; sybil attack; internet integrated WSN.
Efficient Routing Algorithm for improving the Network performance in Internet of Things
by Vijayakrishna Akula, Anny Leema
Abstract: In the recent years, many routing protocols have been developed for Internet of Things (IoT) which reduces the delay and network congestion. However, in some urgent situations, the transmission of urgent or priority packets to the destination with in the specified time are compulsory. The tradition routing methods explores all the paths from source to destination which leads to longer paths and doesnt guarantee the delivery of priority packets. This paper concentrates on developing the priority based event detection routing scheme in IoT. This method analyses the arrival packets and forwards to the destination by finding the shortest path with queue difference. The priority packets which arrive at the priority queue having minimum deadline is selected. The regular packets are followed with their normal queue policy. The experimental results proved that proposed method achieved 34% less end to end delay and 26% high accuracy in throughput compared to the other existing algorithms.
Keywords: Routing; Priority packets; Sensor networks; Internet of Things; Event detection.
Cognitive decision engine design for cognitive radio networks using gravitational search algorithm and flower pollination algorithm
by Badr Benmammar
Abstract: In cognitive radio networks, the real-time setting of the transmission parameters required by the cognitive engine according to the quality of service requested by the cognitive users has become an essential task. This adjustment is becoming increasingly difficult in OFDM-based cognitive radio networks because of the existence of a large number of decision variables to be optimized for multi-carrier systems. For decision making, the cognitive engine in OFDM-based cognitive radio networks uses optimization algorithms. However, in order to reduce the complexity and obtain a resource allocation in a reasonable time, cognitive radio networks use artificial intelligence techniques and in particular metaheuristics. We analyze in this article the performances of two recent metaheuristics namely gravitational search algorithm and flower pollination algorithm in OFDM-based cognitive radio networks. Simulation results show that FPA has surpassed GSA in terms of Fitness. In contrast, GSA outperformed FPA in terms of execution time. On the other side, FPA and GSA outperform genetic algorithms in terms of solution quality (fitness) with improvements reaching 10% and 7% respectively and prove their efficiencies in order to support three modes of transmission of the cognitive user.
Keywords: CRN ; OFDM ; QAM ; PSK ; GSA ; FPA ; GA.
Policy based Heterogeneous Server Utilization using Controller Framework
by Aditi Bankura, Anirban Kundu
Abstract: In this paper, authors have proposed a controller based framework having transmission flow for query search and/or query responses. In this approach, total structure is divided into number of levels, and each level has two set of controllers. Servers are worked together in each set of controllers. Servers are heterogeneous in nature based on functionality and configurations. Server selection in each level, communication establishment, and transmission of information between two servers placed at two consecutive levels are three major tasks to be executed for entire query search processing. Several policies are proposed for communication establishment and transmission of information between servers with consideration of risks management. Several load management strategies have been proposed for server selection dynamically from set of available servers having distinct loads using load balance factor. In this paper, we have also introduced a procedure to follow two separate paths for transmission of search query and query response to avoid congestion in network to achieve minimum delay in query response.
Keywords: Query Searching; Heterogeneous Servers; Packet Formation Policy; Data Migration Policy; Data Block Placement Policy; Failure Policy; Data Block Replication Policy; Server Feedback Policy; Entry Controller; Exit Controller; Server Pool.
On the Minimization of Resource Utilization for Cost Reduction in Space Division Multiplexing Based Elastic Optical Networks
by Sridhar Iyer
Abstract: In the current work, for a Space Division Multiplexing (SDM) based Elastic Optical Network (EON) (SDM-b-EON), we formulate a routing, modulation format, spatial granularity , and spectrum assignment (RMFSpGlSA) problem which aims to minimize the overall network cost by reducing the resource (i.e., wavelength selective switches (WSSs), Lasers, and spectrum) usage. Initially, RMFSpGlSA is formulated as a joint integer linear program (J-ILP) model (namely, J-ILP-RMFSpGlSA) following which, to obtain better convergence and reasonable execution times; J-ILP is split as a RMFSpGl+SA problem (namely, ILP-RMFSpGl+SA) which successively solves the RMFSpGl and the SA problems. Next, considering realistic network topologies and parameters, extensive simulations are conducted to evaluate performances of the two formulated ILP models with an aim to find the best spatial granularity value under various conditions.
The obtained results demonstrate that when the unit cost ratio of the WSSs and the frequency slots (FSs), and the lasers and the FSs is low (e.g., 0.01) then, compared to the WSSs and the Lasers, there occurs more preservation of the spectrum, and a fine value (e.g., 8) is chosen more number of times compared to a coarse value (e.g., 12) which is always chosen for higher values of unit cost ratio of the WSSs and the FSs, and the lasers and the FSs. Further, a coarse spatial granularity value does not have a major effect on the required FSs amount; however, it significantly impacts the required WSSs and Lasers amount which implies that only when equal importance is imposed on the requirement of all the resources, a coarse spatial granularity value is the best value. It is also observed that the fine values of spatial granularity are mostly chosen with the widening of the guardband width values, and for a guardband width value of 50 GHz, a low value (e.g., 8) is only chosen. Also, the obtained results show that with an increase in the mean bit-rate values of the demands, a coarse value of spatial granularity is mostly chosen. Finally, all the results demonstrate that ILP-RMFSpGl+SA obtains similar performance when compared to J-ILP-RMFSpGlSA simultaneously requiring much lesser execution times.
Keywords: Elastic optical networks; space division multiplexing; ILP; switching; resource allocation.
Efficient IPv4-IPv6 translation mechanism for IMS using SIP proxy
by Ali Abdulrazzaq, Alhamza Munther, Supriyanto Praptodiyono
Abstract: Next-generation IP Multimedia Subsystem (IMS) has a promise future in Internet technologies. Technically, IMS utilizes Session Initiation Protocol (SIP) for call communication. Potentially, SIP clients might reside in coexistence network family like IPv6 and/or IPv4. The coexistence of SIP clients considered a serious issue in SIP communication and IPv6 migration in general. Specifically, when IPv6 client try to send a voice call toward IPv4 client, the call will fail or end up with incomplete message. In this paper a SIP-Proxy IP Translator (SPIPT) is proposed to translate SIP call between from IPv6 to IPv4 and vice versa. The proposed solution comes to insure successive connectivity in term of IP version compatibility. The experiment shows that SIP proxy performs with acceptable CPU usage, throughput, and Call Response Time parameters. In sum, the solution aims to reduce call setup complexity and leverages user experience which in turn accelerates IPv6 transition.
Keywords: SIP; IPv6; SIP over IPv6; IPv4-to-IPv6; SIP Service Provider.
The Study of Dynamic Resource Allocation on Aggregation of Unlicensed Spectrum in LTE-A Networks
by Wu Jung-Shyr
Abstract: The 3GPP formulated the fourth-generation LTE-Advanced specifications, in which Carrier Aggregation technology can increase the data transmission rate by aggregating continuous and non-continuous carriers to meet the transmission needs of a large number of users.
However, users demand for multimedia network application services continues to increase and makes the licensed spectrum more and more overwhelming. Therefore, this article hopes to combine the licensed and unlicensed spectrum to provide a wider data channel with higher data transmission. We focus on improving the throughput of the downlink system, and propose a genetic algorithm to optimize the weights which referring to the carrier unit channel quality and load conditions to select the most suitable carrier unit for the user. Afterwards, resource allocation methods are presented for the different traffic of GBR and Non-GBR effectively. Finally, we show the simulation results to prove that the proposed method is effective in improving system throughput and user satisfaction.
Keywords: LTE-A; Carrier aggregation; Genetic algorithm
; resource allocation.
ICCO: Immune clustering based coverage optimization algorithm in wireless sensor networks
by Hongbing Li, Xiaolong Liu, Meng Huang, Qiang Chen, Liwan Chen
Abstract: Characteristics of network itself and unpredictability of its working scenario may greatly affect the clustering topology and coverage performance, furtherly affect transmission reliability and robustness of the network. Topology control and coverage optimization are the prior issues needed to be solved in wireless sensor network which can affect key performance of whole network. Biological immune algorithm is adopted as a novel effective method to the issues of clustering topology control and coverage optimization in networks deployed by the static and movable nodes. Immune Clustering and Coverage Optimization algorithm(ICCO) is proposed which includes Immune Clustering Optimization algorithm(IClO)and Immune Coverage Optimization algorithm (ICoO). First, Immune efficient clustering is completed in the scenario of static senor nodes and then hierarchical clustering topology control is established. Then network coverage is optimized through dynamically and iteratively adjusting the positions of mobile sensor nodes by ICoO which is a multi-objective optimization issue. Network coverage model and energy consumption model is established to analyze the network performance including algorithms convergence, energy consumption and network area coverage. Simulations show that ICCO has realized the maximum coverage based on the robust immune topology with improved performance of fault tolerance by adjustment of movable nodes.
Keywords: Wireless sensor networks; Immune clustering; Coverage optimization; Immune algorithm.
Dynamic Power Management Modeling of a Wireless Sensor Node
by Rakhee Kallimani, Sridhar Iyer
Abstract: Currently there is a growing attention to design low power and energy-efficient nodes for Wireless Sensor Networks. The critical issue which captures the attention of the researchers is the energy constraint and the lifetime of individual nodes of the network. Among the many power management techniques, Dynamic Power Management (DPM) is the most promising technique to control and save the usage of energy of the node and enhance the lifetime. The article proposes an analyzer based event driven sensor node modeled using SimEvents. The model demonstrates the stochastic behavior of an input event arrival with First In First Out Queue, and a single server. The article employs Semi-Markov based DPM to anlayse the power behavior of the sensor node. The developed model is analyzed for the power consumption and the lifetime as the performance metrics. The results prove that factors such as arrival rate and change detection probability affect the Lifetime and Power consumption of an individual node. It is observed that maximum of 237 mW of power is consumed by the node for 85 events/hour and is lasts for 78 days. Further, the effect of event arrival and the change detection probability on the model is also analyzed.
Keywords: Dynamic Power Management; Wireless Sensor Node; Semi-Markov model.
A cross encryption scheme for data security storage in cloud computing environment
by Haiyan Kang, Jie Deng
Abstract: Cloud computing is one of the popular technologies in the development of information technology. Cloud computing not only provides users with high-performance computing, but also meets the needs of large-scale data storage. However, because the storage service provided by cloud computing is completely transparent to users, users can not understand whether their data is safe in the cloud computing environment. The resulting distrust has brought great obstacles to the development of cloud computing. Therefore, this paper first describes the basic knowledge and system architecture of cloud storage, and analyzes the development status of cloud storage. Secondly, in order to ensure the storage security of user data in the cloud computing environment, this paper studies the data encryption algorithm, and proposes a cross encryption scheme of data security storage in the cloud computing environment. Finally, the scheme is compared with the traditional hybrid encryption method. The experimental results show that the scheme has the advantages of good encryption and decryption effect, fast execution speed and high security. It is an ideal scheme for data security storage in cloud computing environment.
Keywords: cloud computing; data encryption; DES; RSA; cross encryption.
Practical and Scalable Access Control Mechanism for Wireless Sensor Networks
by Ummer Khan, Ajaz Hussain Mir
Abstract: The Access Control Mechanism is a necessary security primitive for deploying a new node within the resource-constrained WSN. The mechanism prevents malicious node deployment, which could disrupt network operations entirely. In addition to accommodating the resource-constrained nature of WSN, the design of the new node access control method must also meet specific security and functional specifications. In literature, new node access control schemes have been proposed for WSN, focusing on efficiency and security strength. However, less attention is given to the functional specification of scalability and independence from time synchronisation. In this paper, an ECC-based new node access control is presented. Besides being computationally effective and secure, the scheme is scalable and doesn't have time synchronization issues. The proposed scheme's security strength and correctness have been proven using BAN logic and the Random Oracle Model. Simulations on AVISPA and Scyther tools have been performed for automatic security verification of the proposed method. The proposed scheme has also been programmed on TinyOS to perform simulation on the TOSSIM simulator and test-bed implementation on MicaZ motes.
Keywords: Wireless Sensor network ;Access Control ;Authentication ;Key establishment; Elliptical curve Cryptography; AVISPA; TinyOS; TinyECC.
Secure and Verifiable Outsourcing of Euclidean Distance and Closest Pair of Points with Single Untrusted Cloud Server
by Shilpee Prasad, B.R. Purushothama
Abstract: Due to the resource constraints, often client has to outsource the computation to the untrusted cloud service provider. As cloud service providers are often untrusted, the result of the computation should be verified for the correctness. Also, the cost of verification should be less than the cost of actual computation. In this paper, we address the problem of verifying the computation of a geometric problem. In particular, we address the problem of verifying the Euclidean distance and closest pair of points returned by the single untrusted cloud service provider. We have designed verification schemes for outsourcing Euclidean distance and closest pair of points. We have proved that the proposed scheme has negligible server cheating probability. Also, the proposed scheme preserves the privacy of the outsourced data. We have implemented the closest pair of points verification scheme and show that the cost of verification is very less compared to actual computation cost. Also, compared to existing scheme the proposed scheme has less server cheating probability.
Keywords: Outsource computation; Closest pair of points; Euclidean distance;\r\nPrivacy preserving; Cloud service provider.
RAD: Reinforcement Authentication Model based on DYMO Protocol for MANET
by Rushdi Hammareh, Mohammed Ayyad, Mohammed Abutaha
Abstract: This article aimed to develop a new model based on DYMO protocol where a modification was proposed to route discovery and route maintenance processes. In route discovery process we made an authentication process between the nodes by using MD5 hashing algorithm, then we used reinforcement learning to improve the route maintenance process based on machine learning approach. At the end we used Diffie-Hellman key management to exchange the secret key to encrypt and decrypt the data between Source S and Destination D.
When we tested the proposed protocol, the results show improvement in the performance of MANETs, despite the little increased in the end to end delay in comparison with DYMO protocol. This is due to the overheads in authentication and encryption processes.
Keywords: MANET; DYMO; authentication; reinforcement; security; encryption; hashing; key distribution; nodes; path.
Research on Personalized Privacy-preserving Model of Multi-Sensitive Attributes
by Haiyan Kang, Yaping Feng, Xiameng Si, Kaili Lu
Abstract: In order to protect user information from being leaked, as far as possible to improve the availability of published data and realize the safe and efficient information sharing. Aiming at the anonymous privacy-preserving of multi-sensitive attribute data release in logistics industry, this paper proposes a Personalized privacy-preserving model of Multi-Sensitive attributes with Weights Clustering and Dividing (PMSWCD) by analyzing existing model. Firstly, according to the different needs of users, the corresponding weight is set for each sensitive attribute value to realize personalization and then weighted clustering. Secondly, divide the records according to the weighted average value, and select records to establish a group that satisfies l-diversity. Finally, release data based on the idea of multi-dimensional bucket. Through experimental analysis, compared with WMBF algorithm, the release ratio of important data of PMSWCD algorithm proposed in this paper is significantly improved, reaching more than 95%, which improves the availability of data.
Keywords: Multi-Sensitive attributes; data release; personalized; privacy-preserving; weights clustering; dividing; multi-dimensional bucket; l-diversity.
Special Issue on: Blockchain for Cognitive Wireless Communication Networks
Congruent Fine-Grained Data Mining Model for Large-Scale Medical Data Mining
by Arthi Jaya Kumari J, Muhammad Rukunuddin Ghalib
Abstract: Electronic medical data management is eased with the integration of communication technologies and the cloud/ Internet of Things (IoT) platform in recent years. The organization and mining of the data from massive repositories is a complex and time-consuming process. However, the exploitation of such massive information requires large-scale analytical procedures by accounting its significance. This article introduces congruent fine-grained data mining (CFDM) model for reducing the complexities in large-scale medical data handling. This model identifies the independent and relation-based repositories for matching the request queries in the data retrieval process. By using a classification decision-tree, the identifications are performed to improve the retrieval rate. In this classification tree, the independent and relation-based data are first analyzed for their matching consistencies. By pursuing this process, the non-matching query-data satisfying the relevance condition are grouped into a new relationship based classification. This helps to improve the matching and retrieval rate preciously in the consecutive mining instances. The proposed model improves retrieval responses, retrieving time, complexity, and data availability.
Keywords: Big Data; Classification Learning; Decision Tree; Data Mining; Medical Data.
Efficient Authentication Method using Binary Search Tree with Multi-Gateway in Wireless IoT
by Anita Chaudhari, Rajesh Bansode
Abstract: In recent days, IoT played a major part on the worldwide network. Maintaining security along with privacy of IoT nodes are the main challenge in IoT, as IoT devices are connected and operated using the Internet. Most of the authors had used different technologies for authentication like username, password, OTP, Secret key, RFID, authentication schemes implemented using a single factor, multifactor parameter which are discussed in the review section. But, they continue to suffer from few drawbacks like its adaptability to real time applications that threaten users' data protection. They also possess challenges namely forgotten, stolen, and shared with another user who is unauthorized. Therefore, a strong authentication mechanism is required, so the user can get direct access of sensor information. So, to achieve it, our research concentrates on a unique authentication scheme. The primary goal of this research is to find whether an authenticated user is traveled through and , to find whether the registered sensor is used through and . The security attacks and data hacking are handled by the proposed technique with Binary Search Trees (BST).In our research, several experiments with a different scenario like for authorized and unauthorized user has been performed and the outcome is compared with the existing methods. Based on results, the proposed work outperforms the existent method concerning users, the time required for , and sensor, communication cost, energy cost on the sensor, Packet Delivery Ratios, End-to-End delay (EED), along with throughput.
Keywords: Internet of Things (IoT); Wireless Sensor Networks (WSNs); authentication; GWN; multi-gateway; malicious attack; IoT; BST.
BLOCKCHAIN BASED SYSTEM FOR STORAGE UTILIZATION AND SECURE SHARING OF EHR DATA
by Anjana S. Chandran
Abstract: The main hindrances for the development of BlockChain (BC) are the vast storage volume. Thus, finding a way to optimizing the storage mechanism to release the burden has become an important issue. Nevertheless, solely relying on a specific cloud storage supplier has several potentially serious issues, say vendor lock-in, availability, along with security. To tackle this issue, this paper proposed an effectual BC-centered scheme aimed at storage utilization with respect to Data Deduplication (DD) as well as the secure sharing of Electronics Health Records (EHR) data betwixt several entities involving patients, research institutions, as well as semi-trusted Cloud Servers (CS). And in the interim, it employs the memory via the DD concept. In this, the Stribog hashing algorithm creates the Hash Code (HC) for the uploaded file. To evade storing duplicate copies of data, DD is checked centered on this algorithm. Presently, the system utilizes the Modified Ciphertext-Policy Attribute-Based Encryption (MCP-ABE) for amassing data in the distributed cloud in an encrypted format to guarantee security. Next, the Weight and Exhaustiveness-based Harris Hawks Optimization (WEH2O) selects the Distributed CS (DCS). At last, the data are securely amassed in a BC-centered cloud that also renders security. Centered on the experimentations outcomes, the proposed work offered a better performance analogized to the other data transmission.
Keywords: Deduplication; Electronic Health Record (EHR); Length Shift Cipher; Stribog Algorithm; Modified Ciphertext Policy-Attribute Based Encryption (MCP-ABE); and Weight and Exhaustiveness based Harris Hawks Optimization (WEH2O).
SECURE DYNAMIC BITS STANDARD SCHEME IN PRIVATE CLOUD ENVIRONMENT
by Ghanshyam Gagged, Jaishakti S M
Abstract: Cloud computing is a progressively prevalent prototype for retrieving the resources for computing purposes, data protection is a very significant security issue because transferring data from organizations to remote machines is required if there is no guarantee of data protection from the cloud service providers. This paper suggests a secure dynamic bits standard (SDES) algorithm for transferring the data between, cloud service provider (CSP), data provider (DP), and data user (DU). The minute the data provider uploads files, it automatically uploaded to a local upload folder. Then, a process of encryption is initiated using SDES algorithm the encryption time taken was 0.003 seconds this encrypted file is uploaded into dropbox, before uploading the file into dropbox, an auto resource allocation process is commenced automatically to store the uploaded file into that resource, the cloud service provider can able to decide whether the data provider files approved or rejected. If it is approved then, those files are visible to the data users, otherwise, the files are blocked. To download the files, the data user is utilized to send the private key request to the cloud service provider, after the private key file gets produce immediately it gets sent to the data user. Then, only data user can download the files the download time for the proposed SDES is 0.2 seconds also an attacker is monitored via Session Tracking
Keywords: Cloud Security; SDES algorithm; Encryption & Decryption mechanism; Hacker attack; Auto resource allocation technique.
Enhanced-kNN(M-kNN) based Outlier Detection and Sensor Data Aggregation for Large Data Streams in the IoT-Cloud
by Sampath Kumar Y R, Champa H N
Abstract: IoT is a technology that facilitates several applications of the modern age. Wireless sensors gather real data about IoT applications. Due to their dynamic nature, a large number of sensor data results in data outliers. Sensor data determines the scope of IoT systems, whereas redundant data and outliers can significantly reduce their productivity. Detection of data outliers in early-stage makes the system robust and it also guarantees safety within an IoT ecosystem. Furthermore, redundant and pervasive deployment of wireless Sensor Nodes (SN) affects the sensor data acquisition mechanism. Usually, IoT objects have limited resources. The large-scale dataset containing valuable data requires exploring the nature of real data set by utilizing Dimensionality Reduction (DR) and classification techniques. An advanced data aggregation (DA) technique can decrease the number of total data transmissions and facilitate data accuracy. Here, a data analysis framework is suggested for DA and Outlier Detection (OD) by employing a modified K nearest neighbor (MKNN) algorithm. Further, the proposed methodology is analyzed and compared with the existing Recursive Principal Component analysis (R-PCA) technique with regard to recovery error rate as well as Energy Consumption (EC) via testing Intel lab together with NDBC-TAO data. Via varying the cluster size, the techniques are compared. As of the outcome, it can well be found that the proposed MKNN attains the lowest relative error and lowest EC for all number of cluster size for both Intel and NDBC-TAO data. The proposed model is crucial for exploring the sensor data and predicting future events based on observed sensor data analysis.
Keywords: Data abstraction; Data acquisition; Data aggregation; IoT-Cloud; Outlier detection.
Processing Power Sharing Using a Gadget Power Save For Downloading Scientific Research Project
by Akshay Taywade, Dr.Sasikala R
Abstract: In Todays Era as users had become more uphill and expect to run compute intensive apps in their smartphone devices. Mobile Cloud Computing (MCC) thus combines mobile computing and Cloud Computing (CC) in order to use offloading techniques to expand mobile computer capabilities.Computer offloading solves Smart Mobile Devices (SMD) limitations such as limited computing power, limited battery life and limited storage space by distributing output and workload to other rich systems with enhanced efficiency and resources. For data modelling and analysis, scientific research also need a large amount of computing power. This paper explains about the donation of processing power from unused smartphone computing power to the mobiles that need to download projects from medicine, astronomy, geology, and physics through mobile web services. This is accomplished by developing a cellular gadget called Power Save that download and coordinate the projects to be downloaded during the dormant condition of the mobile. Once the project is downloaded, the status of project server is changed and a new task is assigned. This gadget based processing power sharing would be assistive in saving mobiles battery life and performance level of CPU. The proposed gadget is compared against certain existing applications such as HTC power to give-BOINC.
Keywords: Cloud computing; SMDs; power sharing; Power Save;.
High Speed Pre Accumulator and Post Multiplier for Convolution Neural Networks with Low Power Consumption
by K. Mariya Priyadarshini, R.S. Ernest Ravindran, M. Sujatha, K. T. P. S. Kumar
Abstract: In todays phase of growing technology Convolution Neural Networks (CNN) are all over the place. It is chiefly a thriving segment in machine learning as well as Artificial Intelligences (AI) techniques. CNN need of bulk amount of computing competence and memory with higher frequency range. In this present investigation Pre-Accumulator and Post-Multipliers (PAPM) are proposed which accelerate the processing of image, video and voice. 4-bit multiplier using Carry Save Adder (CSA) is built with 6Transistors-Adder and sutras of Vedic mathematics is constructed. Accumulator of Multiplier and Accumulator are designed with Two Level Edge Triggering Flip-Flops (TLET-FF) to increase bandwidth of the memory. The proposed architecture of Multiply Accumulate (MAC) circuit consumes very less power when compared with that of existing high speed MAC structures. Performance of Accumulator is contrasted with 3 different kinds of Two Level Triggered flip-flops namely 16TLET-FF, 14TLET-FF and 12TLET-FFs. The projected MAC replaces the existing multipliers due its low power together with high frequency of operation.
Keywords: Convolution Neural Networks; Vedic Sutras; Carry Save Adder; Flip-Flop; Multiplier and Accumulator.
A One-Dimensional superior logistic map based image encryption
by Supriya Khaitan, Shrddha Sagar, Rashi Agarwal
Abstract: The importance of digital media has been increased in this pandemic; the media\'s security is a huge issue; this led to the development of cryptographic techniques that are secure and fast. Chaos-based image encryption has gained popularity due to its ergodic properties. This paper proposes a 1-dimensional chaotic logistic map cryptography based on Superior iterations. Both the real and imaginary parts of the 1-Dimensionalmap generate the chaotic sequence that is further mixed with key. The new sequence is used for scrambling and diffusion of pixel values of an image. The proposed scheme was evaluated using many measures like NPCR, UACI, MSE, PSNR, and entropy; simulation result shows the proposed technique is immune to statistical, differential crypto-analysis attacks, and occlusion attacks.
Keywords: Chaotic Map; Image Encryption; Logistic Map; Superior Iterations.
Priority based Sencar Deployment Strategy for Mobile Sink Data Gathering in WSN
by Sunita S. Patil, Senthil Kumaran T
Abstract: Data gathering by means of mobile sinks presents novel encounters to wireless sensor network (WSN) applications. Most of the approaches use single mobile sink or data collector which may not cover the entire network in time.The Sencars with multiple antennas select the optimum pair of sensor nodes to gather data simultaneously. In this paper, a priority based Sencar deployment strategy(PSDS) for mobile sink data gathering is proposed. In this scheme, the priority of sensed data determined depending on the urgency and deadline of data. Then one Sencar is deployed for collecting high priority (critical data) by directly visiting to the respective sensors. Another Sencar is deployed for collecting the low priority (non-critical data) from other sensors. Simulation result shows that the proposed PSDS scheme achieves better PDR and higher residual energy with minimum data gathering delay.
Keywords: Wireless Sensor Networks; Sencars; Mobile sink.
Smart Approach To Constraint Programming: Intelligent Backtracking Using Artificial Intelligence
by Heng Du
Abstract: Constrained Programming is the concept used to select possible alternatives from constrained programming; a problem can be modelled in random terms. This paper proposes an AI-assisted Backtracking Scheme (AI-BS) by integrating the generic backtracking algorithm with Artificial Intelligence (AI). The AI-BS is an algorithm using intelligent backtracking (IB) inside a branch and bound context based on linear programming. The detailed study observes that the extreme dual ray associated with the infeasible linear program can be automatically extracted from minimum unfeasible sets. This research also explains the application of the proposed intelligent backtracking (IB) strategy using a branch-and-cut (BC) algorithm, which is named as IBBS. AI-assisted intelligent backtracking utilized to create a smart optimal schedule controller for home energy controllers to manage and optimize the energy consumptions peak hours. The AI-BS gives an optimal schedule for home appliances to limit the total load demand and schedule the domestic device\'s operations.
Keywords: Artificial Intelligence; Backtracking; Branch-and-Bound Problem; Branch-and-cut; Constrained Programming; Smart home electricity controller.
Internet of Vehicle Things Communication Based on Big Data Analytics Integrated Internet of Things
by Ruiwei Chen, BalaAnand Muthu
Abstract: Automobile industries\' rapid development on modern wireless vehicle communication among vehicles, pedestrians, and roadside information units has been termed as the Internet of Vehicles (IoV). The significant challenges of the IoV include vehicle data management and congestion in the network. In this research, Big data analytics integrated Internet of Things framework (BDA-IoTF) is proposed to process the data received from the roadside units to minimize congestion and optimized data management. Further, the vehicle data has been analyzed for several conditions that help to analyze the network congestion. Based on the congestion level, BDA-IoTF helps evaluate the vehicles\' performance in correlation with data management. This Big Data analytics give immense support in segregation, management, and data collection based on IoT, by sending data directly to the database using Wireless radio frequency Technology. The proposed BDA-IoTF has been validated based on the optimization parameter, which outperforms conventional methods.
Keywords: Internet of Things; Internet of Vehicles; roadside unit; sensors; big data analytics; and congestion.
Machine Learning-based Security Active Defense ModelSecurity Active Defense Technology in the Communication Network
by Linjiang Xie, Feilu Hang, Wei Guo, Yao Lv, Wei Ou, C. Chandru Vignesh
Abstract: Nowadays, there is anticipated exponential growth in the number of internet-enabled devices, which will increase cyber threats across an expanding attack surface area. For guaranteeing network security, this study proposes the Machine Learning-based Security Active Defense Model (MLSADM). Machine learning (ML) is how Artificial Intelligence learns patterns that lead to abnormal behavior. This occurs when an Artificial Intelligence system or neural network is deceived into imperfectly recognizing or intentionally adapting the input. An emerging type of attack and a collaborative attack is measured in the attack and defense situation. Experiments have been carried out with the dynamic (learning) attacker of a static (fixed) defender, static attackers, and dynamic attackers. The findings show that the proposed model enhances network security with high accuracy in network abnormal behavior detection compared to other popular methods.
Keywords: Communication Network; Security Active Defense Technology; Machine learning; Network Security.
Trust-based model for data protection and security in smart cities
by Jun Gao, Manas Ranjan Pradhan, Sandeep Kumar. M
Abstract: Different emerging innovations have been applied to develop the infrastructure for smart cities. IoT is a fast-moving technology that displays its embodiments for the promotion of humanity for prosperous and better intelligent city infrastructure. Smart City has been created by the emergence of intelligent devices on the internet of things. Smart City is suffering from possible privacy risks despite increased service efficiency. Therefore the Trust-based Security Maintenance (TBSM) model has been proposed to enhance the privacy and security aspects of knowledge management interface in many Smart cities. A trust-based framework ensures the necessary protection in smart city applications for the sensitive application development interface. Besides, a trust-based framework is enabled by big data processing to enhance data scalability and usability depending on their accompanying storage site. Security Maintenance model is developed to customise the interface for the data processing of different smart city systems for usability and privacy problems.
Keywords: data protection; security; privacy; smart cities; Internet of Thing (IoT).