In view of the security weakness in resisting the active attacks by malicious nodes in mobile ad hoc networks,the trust metric is introduced to defend those attacks by loading a trust model on the previously proposed ...In view of the security weakness in resisting the active attacks by malicious nodes in mobile ad hoc networks,the trust metric is introduced to defend those attacks by loading a trust model on the previously proposed Distance-Based LAR.The improved Secure Trust-based Location-Aided Routing algorithm utilizes direct trust and recommendation trust to prevent malicious nodes with low trust values from joining the forwarding.Simulation results reveal that ST-LAR can resist attacks by malicious nodes effectively;furthermore,it also achieves better performance than DBLAR in terms of average end-to-end delay,packet delivery success ratio and throughput.展开更多
Routing strategies and security issues are the greatest challenges in Wireless Sensor Network(WSN).Cluster-based routing Low Energy adaptive Clustering Hierarchy(LEACH)decreases power consumption and increases net-wor...Routing strategies and security issues are the greatest challenges in Wireless Sensor Network(WSN).Cluster-based routing Low Energy adaptive Clustering Hierarchy(LEACH)decreases power consumption and increases net-work lifetime considerably.Securing WSN is a challenging issue faced by researchers.Trust systems are very helpful in detecting interfering nodes in WSN.Researchers have successfully applied Nature-inspired Metaheuristics Optimization Algorithms as a decision-making factor to derive an improved and effective solution for a real-time optimization problem.The metaheuristic Elephant Herding Optimizations(EHO)algorithm is formulated based on ele-phant herding in their clans.EHO considers two herding behaviors to solve and enhance optimization problem.Based on Elephant Herd Optimization,a trust-based security method is built in this work.The proposed routing selects routes to destination based on the trust values,thus,finding optimal secure routes for transmitting data.Experimental results have demonstrated the effectiveness of the proposed EHO based routing.The Average Packet Loss Rate of the proposed Trust Elephant Herd Optimization performs better by 35.42%,by 1.45%,and by 31.94%than LEACH,Elephant Herd Optimization,and Trust LEACH,respec-tively at Number of Nodes 3000.As the proposed routing is efficient in selecting secure routes,the average packet loss rate is significantly reduced,improving the network’s performance.It is also observed that the lifetime of the network is enhanced with the proposed Trust Elephant Herd Optimization.展开更多
In this paper, we consider the scalable of wireless sensor networks with trust-based security. In our setting, the nodes have limited capability so that heavy computations are not suitable. So public key cryptographic...In this paper, we consider the scalable of wireless sensor networks with trust-based security. In our setting, the nodes have limited capability so that heavy computations are not suitable. So public key cryptographic algorithms are not allowed. We focus on the scalability of the network and proposed new testing algorithms and evaluation algorithms to test new nodes added, which give them reasonable values of trust. Based on these algorithms, we proposed new components for trust management system of wireless sensor networks.展开更多
Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade...Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade substantially under malicious interference.We introduce iSTSP,an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust,precise synchronization even in hostile environments:(1)trust preprocessing that filters node participation using behavioral trust scoring;(2)anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time;(3)reliability-weighted consensus that prioritizes high-trust nodes during time aggregation;and(4)convergence-optimized synchronization that dynamically adjusts parameters using theoretical stability bounds.We provide rigorous convergence analysis including a closed-form expression for convergence time,and validate the protocol through both simulations and realworld experiments on a controlled 16-node testbed.Under Sybil attacks with five malicious nodes within this testbed,iSTSP maintains synchronization error increases under 12%and achieves a rapid convergence.Compared to state-ofthe-art protocols like TPSN,SE-FTSP,and MMAR-CTS,iSTSP offers 60%faster detection,broader threat coverage,and more than 7 times lower synchronization error,with a modest 9.3%energy overhead over 8 h.We argue this is an acceptable trade-off for mission-critical deployments requiring guaranteed security.These findings demonstrate iSTSP’s potential as a reliable solution for secure WSN synchronization and motivate future work on large-scale IoT deployments and integration with energy-efficient communication protocols.展开更多
Wireless Sensor Networks(WSN)are commonly used to observe and monitor precise environments.WSNs consist of a large number of inexpensive sensor nodes that have been separated and distributed in different environments....Wireless Sensor Networks(WSN)are commonly used to observe and monitor precise environments.WSNs consist of a large number of inexpensive sensor nodes that have been separated and distributed in different environments.The base station received the amount of data collected by the numerous sensors.The current developments designate that the attentFgion in applications of WSNs has been increased and extended to a very large scale.The Trust-Based Adaptive Acknowledgement(TRAACK)Intrusion-Detection System for Wireless Sensor Networks(WSN)is described based on the number of active positive deliveries and The Kalman filter used in Modified Particle Swarm Optimization(MPSO)has been proposed to predict knot confidence.Simulations were run for non-malicious networks(0%malicious)and different percentages of malicious nodes were discussed.The findings suggest that the proposed method TRAACK Modified Particle Swarm Optimization(MPSO)packet delivery rate outperforms TRAACKPSO by 3.3%with 0%malicious nodes.Similarly,the packet delivery rate of TRAACKMPSO is 30%malicious,3.5%better than TRAACKPSO in WSN.展开更多
Cloud computing belongs to a set of policies,protocols,technologies through which one can access shared resources such as storage,applications,net-works,and services at relatively low cost.Despite the tremendous advan...Cloud computing belongs to a set of policies,protocols,technologies through which one can access shared resources such as storage,applications,net-works,and services at relatively low cost.Despite the tremendous advantages of cloud computing,one big threat which must be taken care of is data security in the cloud.There are a dozen of threats that we are being exposed to while avail-ing cloud services.Insufficient identity and access management,insecure inter-faces and Applications interfaces(APIs),hijacking,advanced persistent threats,data threats,and many more are certain security issues with the cloud platform.APIs and service providers face a huge challenge to ensure the security and integ-rity of both network and data.To overcome these challenges access control mechanisms are employed.Traditional access control mechanisms fail to monitor the user operations on the cloud platform and are prone to attacks like IP spoofing and other attacks that impact the integrity of the data.For ensuring data integrity on cloud platforms,access control mechanisms should go beyond authentication,identification,and authorization.Thus,in this work,a trust-based access control mechanism is proposed that analyzes the data of the user behavior,network beha-vior,demand behavior,and security behavior for computing trust value before granting user access.The method that computes thefinal trust value makes use of the fuzzy logic algorithm.The trust value-based policies are defined for the access control mechanism and based on the trust value outcome the access control is granted or denied.展开更多
This paper focuses on developing an intrusion prevention and detection Vehicular Ad Hoc Network system by expert systems.The node data are composed of online sources.The gathered node data is fed to the extraction pha...This paper focuses on developing an intrusion prevention and detection Vehicular Ad Hoc Network system by expert systems.The node data are composed of online sources.The gathered node data is fed to the extraction phase which can be done by using the autoencoder model.The extraction of features was given to the selection of feature stage to select the optimal features using the Beetle-Whale Swarm Optimization.The selected accurate features are employed in the intrusion detection stage with the help of a hybrid Deep Neural Network and Bidirectional Long Short Term Memory approach for the detection of network intrusion.The intrusion prevention takes place with the Trust-based routing protocol,where the malicious node is prevented by optimally selecting the routing path using the same B-WSO.The experimental analyses are performed to check the efficiency of the developed method by testing with conventional techniques.展开更多
基金supported by National Key Basic Research Program(973 Program) under Grant No.2011CB302903National Natural Science Foundation under Grant No.60873231+1 种基金Key Program of Natural Science for Universities of Jiangsu Province under Grant No.10KJA510035Scientific Research Foundation of NJUPT under Grant No.NY209016,China
文摘In view of the security weakness in resisting the active attacks by malicious nodes in mobile ad hoc networks,the trust metric is introduced to defend those attacks by loading a trust model on the previously proposed Distance-Based LAR.The improved Secure Trust-based Location-Aided Routing algorithm utilizes direct trust and recommendation trust to prevent malicious nodes with low trust values from joining the forwarding.Simulation results reveal that ST-LAR can resist attacks by malicious nodes effectively;furthermore,it also achieves better performance than DBLAR in terms of average end-to-end delay,packet delivery success ratio and throughput.
文摘Routing strategies and security issues are the greatest challenges in Wireless Sensor Network(WSN).Cluster-based routing Low Energy adaptive Clustering Hierarchy(LEACH)decreases power consumption and increases net-work lifetime considerably.Securing WSN is a challenging issue faced by researchers.Trust systems are very helpful in detecting interfering nodes in WSN.Researchers have successfully applied Nature-inspired Metaheuristics Optimization Algorithms as a decision-making factor to derive an improved and effective solution for a real-time optimization problem.The metaheuristic Elephant Herding Optimizations(EHO)algorithm is formulated based on ele-phant herding in their clans.EHO considers two herding behaviors to solve and enhance optimization problem.Based on Elephant Herd Optimization,a trust-based security method is built in this work.The proposed routing selects routes to destination based on the trust values,thus,finding optimal secure routes for transmitting data.Experimental results have demonstrated the effectiveness of the proposed EHO based routing.The Average Packet Loss Rate of the proposed Trust Elephant Herd Optimization performs better by 35.42%,by 1.45%,and by 31.94%than LEACH,Elephant Herd Optimization,and Trust LEACH,respec-tively at Number of Nodes 3000.As the proposed routing is efficient in selecting secure routes,the average packet loss rate is significantly reduced,improving the network’s performance.It is also observed that the lifetime of the network is enhanced with the proposed Trust Elephant Herd Optimization.
文摘In this paper, we consider the scalable of wireless sensor networks with trust-based security. In our setting, the nodes have limited capability so that heavy computations are not suitable. So public key cryptographic algorithms are not allowed. We focus on the scalability of the network and proposed new testing algorithms and evaluation algorithms to test new nodes added, which give them reasonable values of trust. Based on these algorithms, we proposed new components for trust management system of wireless sensor networks.
基金this project under Geran Putra Inisiatif(GPI)with reference of GP-GPI/2023/976210。
文摘Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade substantially under malicious interference.We introduce iSTSP,an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust,precise synchronization even in hostile environments:(1)trust preprocessing that filters node participation using behavioral trust scoring;(2)anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time;(3)reliability-weighted consensus that prioritizes high-trust nodes during time aggregation;and(4)convergence-optimized synchronization that dynamically adjusts parameters using theoretical stability bounds.We provide rigorous convergence analysis including a closed-form expression for convergence time,and validate the protocol through both simulations and realworld experiments on a controlled 16-node testbed.Under Sybil attacks with five malicious nodes within this testbed,iSTSP maintains synchronization error increases under 12%and achieves a rapid convergence.Compared to state-ofthe-art protocols like TPSN,SE-FTSP,and MMAR-CTS,iSTSP offers 60%faster detection,broader threat coverage,and more than 7 times lower synchronization error,with a modest 9.3%energy overhead over 8 h.We argue this is an acceptable trade-off for mission-critical deployments requiring guaranteed security.These findings demonstrate iSTSP’s potential as a reliable solution for secure WSN synchronization and motivate future work on large-scale IoT deployments and integration with energy-efficient communication protocols.
文摘Wireless Sensor Networks(WSN)are commonly used to observe and monitor precise environments.WSNs consist of a large number of inexpensive sensor nodes that have been separated and distributed in different environments.The base station received the amount of data collected by the numerous sensors.The current developments designate that the attentFgion in applications of WSNs has been increased and extended to a very large scale.The Trust-Based Adaptive Acknowledgement(TRAACK)Intrusion-Detection System for Wireless Sensor Networks(WSN)is described based on the number of active positive deliveries and The Kalman filter used in Modified Particle Swarm Optimization(MPSO)has been proposed to predict knot confidence.Simulations were run for non-malicious networks(0%malicious)and different percentages of malicious nodes were discussed.The findings suggest that the proposed method TRAACK Modified Particle Swarm Optimization(MPSO)packet delivery rate outperforms TRAACKPSO by 3.3%with 0%malicious nodes.Similarly,the packet delivery rate of TRAACKMPSO is 30%malicious,3.5%better than TRAACKPSO in WSN.
文摘Cloud computing belongs to a set of policies,protocols,technologies through which one can access shared resources such as storage,applications,net-works,and services at relatively low cost.Despite the tremendous advantages of cloud computing,one big threat which must be taken care of is data security in the cloud.There are a dozen of threats that we are being exposed to while avail-ing cloud services.Insufficient identity and access management,insecure inter-faces and Applications interfaces(APIs),hijacking,advanced persistent threats,data threats,and many more are certain security issues with the cloud platform.APIs and service providers face a huge challenge to ensure the security and integ-rity of both network and data.To overcome these challenges access control mechanisms are employed.Traditional access control mechanisms fail to monitor the user operations on the cloud platform and are prone to attacks like IP spoofing and other attacks that impact the integrity of the data.For ensuring data integrity on cloud platforms,access control mechanisms should go beyond authentication,identification,and authorization.Thus,in this work,a trust-based access control mechanism is proposed that analyzes the data of the user behavior,network beha-vior,demand behavior,and security behavior for computing trust value before granting user access.The method that computes thefinal trust value makes use of the fuzzy logic algorithm.The trust value-based policies are defined for the access control mechanism and based on the trust value outcome the access control is granted or denied.
文摘This paper focuses on developing an intrusion prevention and detection Vehicular Ad Hoc Network system by expert systems.The node data are composed of online sources.The gathered node data is fed to the extraction phase which can be done by using the autoencoder model.The extraction of features was given to the selection of feature stage to select the optimal features using the Beetle-Whale Swarm Optimization.The selected accurate features are employed in the intrusion detection stage with the help of a hybrid Deep Neural Network and Bidirectional Long Short Term Memory approach for the detection of network intrusion.The intrusion prevention takes place with the Trust-based routing protocol,where the malicious node is prevented by optimally selecting the routing path using the same B-WSO.The experimental analyses are performed to check the efficiency of the developed method by testing with conventional techniques.
