International Journal of Computer Network and Information Security @ijcnis
Статьи журнала - International Journal of Computer Network and Information Security
Все статьи: 1148
Статья научная
The Wireless Sensor Network (WSN) is made up with small batteries powered sensor devices with lim-ited energy resources within it. These sensor nodes are used to monitor physical or environmental conditions and to pass their data through the wireless network to the main location. One of the crucial issues in wireless sensor network is to create a more energy efficient system. Clustering is one kind of mechanism in Wireless Sensor Networks to prolong the network lifetime and to reduce network energy consumption. In this paper, we propose a new routing protocol called Fuzzy Based Energy Effi-cient Multiple Cluster Head Selection Routing Protocol (FEMCHRP) for Wireless Sensor Network. The routing process involves the Clustering of nodes and the selection of Cluster Head (CH) nodes of these clusters which sends all the information to the Cluster Head Leader (CHL). After that, the cluster head leaders send aggregated data to the Base Station (BS). The selection of cluster heads and cluster head leaders is performed by using fuzzy logic and the data transmission process is performed by shortest energy path which is selected applying Dijkstra Algorithm. The simulation results of this research are compared with other protocols BCDCP, CELRP and ECHERP to evaluate the performance of the proposed routing protocol. The evaluation concludes that the proposed routing protocol is better in prolonging network lifetime and balancing energy consumption.
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Fuzzy Membership Function in a Trust Based AODV for MANET
Статья научная
Security issues have been emphasized in MANET due to its vulnerability to unauthorised access and unshielded broadcasting nature of communication. In this paper we present a trust based AODV for MANET. The trust takes into account the eligible neighbours based on reliability, residual energy, and speed. Thus our algorithm provides a reliable, energy efficient routing technique. The multi-criteria trust values are calculated using fuzzy-logic. This algorithm is capable of putting aside the selfish nodes. As only trusted neighbours are selected for packet delivery, energy consumption also diminishes because the transmitting node does not need to deliver packets to the untrusted neighbours. Less number of transmissions renders low energy consumption. Absence of selfish nodes in the selected neighbours at every hop provides better packet delivery and hence better throughput.
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Fuzzy rule based inference system for implementation of naval military mission
Статья научная
Naval military units are convoluted frameworks required to work in specific time periods in seaward assignments where support operations are radically restricted. A decline at the time of mission is an analytical fact that can radically impact the mission achievement. The choice of changing a unit to a mission subsequently requires complex judgments including data about the well being status of hardware and the natural conditions. The present system expects to help the choice about changing a unit to a mission considering that ambiguity and unpredictability of information by methods of fuzzy concepts and imitates the selection procedure of a human trained by means of a rule-based inference system. A numerical application is introduced to demonstrate the viability of the approach.
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GAFBone: A New Backbone Construction for Increasing Lifetime in Wireless Sensor Networks
Статья научная
Wireless sensor networks, which have been used in many applications in recent years, consist of tiny sensor nodes with restriction in processing ability and the battery unit. Because of that, one of the crucial problems in this field is power consumption and network lifetime. Geographic Adaptive Fidelity is a routing protocol which tries to reduce energy consumption by powering off unnecessary nodes. In this paper, we proposed a new backbone algorithm for this protocol to saving more energy which causes to improving the lifetime and performance of the networks. The results of simulation show that active grids will be halved approximately.
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GDAR: A Secure Authentication for Dapp Interoperability in Blockchain
Статья научная
Enterprises are adopting blockchain technology to build a server-less and trust-less system by assuring immutability and are contributing to blockchain research, innovation, and implementation. This led to the genesis of various decentralized blockchain platforms and applications that are unconnected with each other. Interoperability between these siloed blockchains is a must to reach its full potential. To facilitate mass adoption, technology should have the ability to transact between various decentralized applications (dapps) on the same chain, integrate with existing systems, and initiate transactions on other networks. In our research, we propose a secured authentication mechanism that enables various decentralized applications on the same chain to interact with each other using a global dapp authentication registry (GDAR). We carried out an in-depth performance evaluation and conclude that our proposed mechanism is an operative authentication solution for dapp interoperability.
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Статья научная
The imbalanced surveillance video dataset consists of majority and minority classes as normal and anomalous instances in the nonlinear and non-Gaussian framework. The normal and anomalous instances cause majority and minority samples or particles associated with high and low probable regions when considering the standard particle filter. The minority particles tend to be at high risk of being suppressed by the majority particles, as the proposal probability density function (pdf) encourages the highly probable regions of the input data space to remain a biased distribution. The standard particle filter-based tracker afflicts with sample degeneration and sample impoverishment due to the biased proposal pdf ignoring the minority particles. The difficulty in designing the correct proposal pdf prevents particle filter-based tracking in the imbalanced video data. The existing methods do not discuss the imbalanced nature of particle filter-based tracking. To alleviate this problem and tracking challenges, this paper proposes a novel fractional whale particle filter (FWPF) that fuses the fractional calculus-based whale optimization algorithm (FWOA) and the standard particle filter under weighted sum rule fusion. Integrating the FWPF with an iterative Gaussian mixture model (GMM) with unbiased sample variance and sample mean allows the proposal pdf to be adaptive to the imbalanced video data. The adaptive proposal pdf leads the FWPF to a minimum variance unbiased estimator for effectively detecting and tracking multiple objects in the imbalanced video data. The fractional calculus up to the first four terms makes the FWOA a local and global search operator with inherent memory property. The fractional calculus in the FWOA oversamples minority particles to be diversified with multiple imputations to eliminate data distortion with low bias and low variance. The proposed FWPF presents a novel imbalance evaluation metric, tracking distance correlation for the imbalanced tracking over UCSD surveillance video data and shows greater efficacy in mitigating the effects of the imbalanced nature of video data compared to other existing methods. The proposed method also outshines the existing methods regarding precision and accuracy in tracking multiple objects. The consistent tracking distance correlation near zero values provides efficient imbalance reduction through bias-variance correction compared to the existing methods.
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GSM Base Stations Location Monitoring using Geographic Information System
Статья научная
Global System for Mobile Communication (GSM) is a digital system developed to meet the desires of the entire public. As the population of a particular area, city or country increases, the number of mobile subscribers increases too. GSM network operators have to reduce congestion on their networks in order to satisfy their subscribers, therefore, a means of monitoring the base stations' locations and the geographical area of where they are located are important factor to achieve this purpose. This work provides a simple step-by-step approach on how to monitor the location of the base stations. A review of GSM and Global Positioning System (GPS) technology and their applications to the Geographic Information System (GIS) are presented. The means of taken the coordinates of base stations using a GPS device is also presented. ESRI's ArcView application software was used to design the map that shows the location of the base station and thereafter was integrated into the web. It concluded with the recommendation to GSM operators in Nigeria. If the recommendations are given necessary attention, the planning and optimization of cell sites will be enhanced and thereby reduce congestion on network. As a result, the performance of Network will improve, and it will give rise to subscribers' satisfaction and increasing profit returns to the operators.
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Galua Field Multipliers Core Generator
Статья научная
An important part of based on elliptical curves cryptographic data protection is multipliers of Galois fields. For based on elliptical curves digital signatures, not only prime but also extended Galois fields GF(pm) are used. The article provides a theoretical justification for the use of extended Galois fields GF(dm) with characteristics d > 2, and a criterion for determining the best field is presented. With the use of the proposed criterion, the best fields, which are advisable to use in data protection, are determined. Cores (VHDL descriptions of digital units) are considered as structural part of based on FPGA devices. In the article methods for cryptoprocessors cores creating were analyzed. The article describes the generator of VHDL descriptions of extended Galois field multipliers with big characteristic (up to 2998). The use of mathematical packages for calculations to improve the quality of information security is also considered. The Galois field multipliers generator creates the VHDL description of multipliers schemes, describes connections of their parts and generates VHDL descriptions of these parts as result of Quine-McCluskey Boolean functions minimization method. However, the execution time of the algorithm increases with increasing amount of input data. Accordingly, generating field multipliers with large characteristic can take frерom a few seconds to several tens of seconds. It's important to simplify the design and minimize logic gates number in a field programmable gate array (FPGA) because it will speed up the operation of multipliers. The generator creates multipliers according to the three variants. The efficiency of using multipliers for fields with different characteristics was compared in article. The expediency of using extended Galois fields GF(dm) with characteristics d > 2 in data protection tools is analyzed, a criterion for comparing data protection tools based on such Galois fields is determined, and the best fields according to the selected criterion when implemented according to a certain algorithm are determined.
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Generalized Galois-Fibonacci Matrix Generators Pseudo-Random Sequences
Статья научная
The article discusses various options for constructing binary generators of pseudo-random numbers (PRN) based on the so-called generalized Galois and Fibonacci matrices. The terms "Galois matrix" and "Fibonacci matrix" are borrowed from the theory of cryptography, in which the linear feedback shift registers (LFSR) generators of the PRN according to the Galois and Fibonacci schemes are widely used. The matrix generators generate identical PRN sequences as the LFSR generators. The transition from classical to generalized matrix PRN generators (PRNG) is accompanied by expanding the variety of generators, leading to a significant increase in their cryptographic resistance. This effect is achieved both due to the rise in the number of elements forming matrices and because generalized matrices are synthesized based on primitive generating polynomials and polynomials that are not necessarily primitive. Classical LFSR generators of PRN (and their matrix equivalents) have a significant drawback: they are susceptible to Berlekamp-Messi (BM) attacks. Generalized matrix PRNG is free from BM attack. The last property is a consequence of such a feature of the BM algorithm. This algorithm for cracking classical LFSR generators of PRN solves the problem of calculating the only unknown – a primitive polynomial generating the generator. For variants of generalized matrix PRNG, it becomes necessary to determine two unknown parameters: both an irreducible polynomial and a forming element that produces a generalized matrix. This problem turns out to be unsolvable for the BM algorithm since it is designed to calculate only one unknown parameter. The research results are generalized for solving PRNG problems over a Galois field of odd characteristics.
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Статья научная
The present paper provides a new mechanism with two stages for efficient authentication based on Honey Comb Polynomial Interpolation (HCPI) and Morphological Border Sorted Pixel Value Difference (MBSPVD) scheme. A simple polynomial interpolation technique on new hexagonal structure called Honey Comb structure (HCS) is used for generating the key of the digital watermark. The polynomial interpolation gives a high secured key, which is difficult to break. HCS is used in the present paper to select pixel positions for generating the Digital Watermark key (DWK). The significant factor of the present method is, the digital watermark is generated by using DWK. The importance of HCS representation is that it possesses special computational features that are pertinent to the vision process. The HCS has features of higher degree of circular symmetry, uniform connectivity, greater angular resolution, and which leads to reduce storage and computation in image processing operations. The DWK is placed in the image by using MBSPVD method. Its guarantees high authentication, robustness, security and copyright protection. The Lagrange Polynomial interpolation (LPI) is used for retrieving the digital watermark from the DWK. The LPI accomplish the aim of image authentication and protection without reducing the image quality. The proposed HCPI-MBSPVD is tested with various attacks and compared with various existing image authentication and copyright protection methods. The comparisons and results indicate the efficacy of the proposed method.
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Genetic Algorithm Based Node Fault Detection and Recovery in Distributed Sensor Networks
Статья научная
Sensor nodes are prone to failure due to energy depletion and some other reasons in Distributed Sensor Networks (DSNs). In this regard fault tolerance of network is essential in distributed sensor environment. Energy efficiency, network or topology control and fault-tolerance are the most important issues in the development of next-generation DSNs. This paper proposes a node fault detection and recovery by using Genetic Algorithm (GA), when some of the sensor nodes faulty in DSN. The main objective of this work is to provide fault tolerance mechanism, which is energy efficient and responsive to network by using GA which is used to detect the faulty of nodes in the network based on the energy depletion of node and link failure between nodes. The proposed fault detection model is used to detect faults at node level and network level faults (link failure and packet error). We have evaluated the performance parameters for the proposed scheme.
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Статья научная
Intrusion detection system is the most important part of the network security system because the volume of unauthorized access to the network resources and services increase day by day. In this paper a genetic algorithm based intrusion detection system is proposed to solve the problem of the small disjunct in the decision tree. In this paper genetic algorithm is used to improve the coverage of those rules which are cope with the problem of the small disjunct. The proposed system consists of two modules rule generation phase, and the second module is rule optimization module. We tested the effectiveness of the system with the help of the KDD CUP dataset and the result is compared with the REP Tree, Random Tree, Random Forest, Na?ve Bayes, and the DTLW IDS (decision tree based light weight intrusion detection system). The result shows that the proposed system provide the best result in comparison to the above mentioned classifiers.
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Genetic Centralized Dynamic Clustering in Wireless Sensor Networks
Статья научная
In order to minimize the energy consumption involved by communications in wireless sensor networks, the use of clustering has proven to be effective. The problem remains to determine the number of cluster-heads, and their distribution in the network to ensure minimal energy consumption and better coverage networks. Unlike Low-Energy Adaptive Clustering Hierarchy algorithm which fixes in advance the number of cluster-heads, and do not guarantee the coverage of the entire network, in this paper, we proposed a genetic centralized dynamic algorithm (GA)-based clustering approach to optimize the clustering configuration (the number of cluster-heads, their distribution and the cluster-members) to limit node energy consumption and the best coverage. The obtained simulation results show that the proposed technique overcomes the Low-Energy Adaptive Clustering Hierarchy algorithm.
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Genetic spectrum assignment model with constraints in cognitive radio networks
Статья научная
The interference constraints of genetic spectrum assignment model in cognitive radio networks are analyzed in this paper. An improved genetic spectrum assignment model is proposed. The population of genetic algorithm is divided into two sets, the feasible spectrum assignment strategies and the randomly updated spectrum assignment strategies. The penalty function is added to the utility function to achieve the spectrum assignment strategy that satisfies the interference constraints and has better fitness. The proposed method is applicable in both the genetic spectrum assignment model and the quantum genetic spectrum assignment mode. It can ensure the randomness of partial chromosomes in the population to some extent, and reduce the computational complexity caused by the constraints-free procedure after the update of population. Simulation results show that the proposed method can achieve better performance than the conventional genetic spectrum assignment model and quantum genetic spectrum assignment model
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Geographic Load Balanced Routing in Wireless Sensor Networks
Статья научная
Recently the application domains of wireless sensor networks have grown exponentially. Traditional routing algorithm generates traffic related to route discovery to destination. Geographic routing algorithms exploit location information well but the problem of congestion and collision throttle its full employment for resource constrained wireless sensor networks. In this paper we present a Geographic Load Balanced Routing (GLBR), explores a technique Load balancing for WSNs which can be a viable solution to the challenges of geographic routing. Load balancing can be realized through two approaches. GLBR defines parameters based on communication overhead at sensor nodes and wireless link status through which load can be balanced across whole network. GLBR approach exploits the existing Geographic Routing approach i.e. Greedy forwarding by considering not only the distance between next hop and destination as single parameter for packet forwarding but also consider overhead at node. When load at a node is high GLBR looks for an alternate option for packet forwarding. Thus GLBR divert traffic to obviate congestion and hence avoid disconnections in the network.
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Getting Obstacle Avoidance Trajectory of Mobile Beacon for Localization
Статья научная
Localization is one of the most important technologies in wireless sensor network, and mobile beacon assisted localization is a promising localization method. The mobile beacon trajectory planning is a basic and important problem in these methods. There are many obstacles in the real world, which obstruct the moving of mobile beacon. This paper focuses on the obstacle avoidance trajectory planning scheme. After partitioning the deployment area with fixed cell decomposition, the beacon trajectory are divided into global and local trajectory. The approximate shortest global trajectory is obtained by depth-first search, greedy strategy method and ant colony algorithm, while local trajectory is any existing trajectories. Simulation results show that this method can avoid obstacles in the network deployment area, and the smaller cell size leads to longer beacon trajectory and more localizable sensor nodes.
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Global Trust: A Trust Model for Cloud Service Selection
Статья научная
Cloud Computing refers to network-based service provided by a large number of computers, sharing computing and storage resources. Combined with on-demand provisioning mechanisms and relied on a pay-per-use business model. The Cloud Computing offers the possibilities to scale rapidly, to store data remotely and to share services in a dynamic environment. However, these benefits can be seen as weaknesses for assuring trust, and providing confidence to the users of service. In this case, some traditional mechanisms to guarantee reliable services are no longer suitable or dynamic enough, and new models need to be developed to fit this paradigm. This study describes the assessment of the trust in the context of Cloud Computing, proposes a new trust model adapted to Cloud environments, and shows some experiments in regards of the proposed solution.
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Graph Structured Data Security using Trusted Third Party Query Process in Cloud Computing
Статья научная
Cloud computing enables the users to outsource and access data economically from the distributed cloud server. Once the data leaves from data owner premises, there is no privacy guarantee from the untrusted parties in cloud storage system. Providing data privacy for the outsourced sensitive data is a challenging task in cloud computing. In this paper we have proposed a Trusted Third party Query Process(TTQP) method to provide data privacy for graph structured outsourced data. This method utilize the encrypted graph frequent features search index list to search the matched query graph features in graph data base. The proposed system has analyzed in terms of different size of data graphs, index storage, query feature size and query execution time. The performance analysis of our proposed system shows, this method is more secure than the existing privacy preserving encrypted Query Graph (PPQG).
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Статья научная
Binary code similarity detection (BCSD) is a method for identifying similarities between two or more slices of binary code (machine code or assembly code) without access to their original source code. BCSD is often used in many areas, such as vulnerability detection, plagiarism detection, malware analysis, copyright infringement and software patching. Numerous approaches have been developed in these areas via graph matching and deep learning algorithms. Existing solutions have low detection accuracy and lack cross-architecture analysis. This work introduces a cross-platform graph deep learning-based approach, i.e., GraphConvDeep, which uses graph convolution networks to compute the embedding. The proposed GraphConvDeep approach relies on the control flow graph (CFG) of individual binary functions. By evaluating the distance between two embeddings of functions, the similarity is detected. The experimental results show that GraphConvDeep is better than other cutting-edge methods at accurately detecting similarities, achieving an average accuracy of 95% across different platforms. The analysis shows that the proposed approach achieves better performance with an area under the curve (AUC) value of 96%, particularly in identifying real-world vulnerabilities.
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Статья научная
Wireless sensor networks (WSNs), which provide sensing capabilities to Internet of Things (IoT) equipment with limited energy resources, are made up of specialized transducers. Since substitution or re-energizing of batteries in sensor hubs is extremely difficult, power utilization becomes one of the pivotalmattersin WSN. Clustering calculation assumes a significant part in power management for the energy-compelled network. Optimal cluster head selection suitably adjusts the load in the sensor network, thereby reduces the energy consumption and elongates the lifetime of assisted sensors. This article centers around to an appropriate load balancing and routing technique by the utilization recently developed of Elephant Herding Optimization (EHO) algorithm that alternates the cluster location amongst nodes with the highest energy. The Scheme considered various parameter residual energy, initial energy and an optimum number of cluster head for the next cluster heads selection. The proposed model increases the lifetime of the network by keeping more nodes active even after the 2700th round. The experiment results of the trials show that the proposed EHO-based CH selection strategy outperforms the cutting-edge CH selection models.
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