Mobile Ad-hoc Networks(MANET)usage across the globe is increas-ing by the day.Evaluating a node’s trust value has significant advantages since such network applications only run efficiently by involving trustable nodes...Mobile Ad-hoc Networks(MANET)usage across the globe is increas-ing by the day.Evaluating a node’s trust value has significant advantages since such network applications only run efficiently by involving trustable nodes.The trust values are estimated based on the reputation values of each node in the network by using different mechanisms.However,these mechanisms have various challenging issues which degrade the network performance.Hence,a novel Quality of Service(QoS)Trust Estimation with Black/Gray hole Attack Detection approach is proposed in this research work.Initially,the QoS-based trust estimation is proposed by using a Fuzzy logic scheme.The trust value of each node is estimated by using each node’s reputation values which are deter-mined based on the fuzzy membership function values and utilizing QoS para-meters such as residual energy,bandwidth,node mobility,and reliability.This mechanism prevents only the black hole attack in the network during transmis-sion.But,the gray hole attacks are not identified which in turn increases the pack-et drop rate significantly.Hence,the gray hole attack is also detected based on the Kullback-Leibler(KL)divergence method used for estimating the statistical mea-sures.Additional QoS metrics are considered to prevent the gray hole attack,such as packet loss,packet delivery ratio,and delay for each node.Thus,the proposed mechanism prevents both black hole and gray hole attacks simultaneously.Final-ly,the simulation results show that the effectiveness of the proposed mechanism compared with the other trust-aware routing protocols in MANET.展开更多
Purpose-With the development of wireless networks and artificial intelligence technology,unmanned aerial vehicle(UAV)clusters are widely used in various fields and cluster intelligence attacks are more harmful.However...Purpose-With the development of wireless networks and artificial intelligence technology,unmanned aerial vehicle(UAV)clusters are widely used in various fields and cluster intelligence attacks are more harmful.However,most methods defending against UAV clusters produce consumption of non-reusable resources.To address this problem,a tethered UAV is adopted to perform active defense against adversary UAV clusters in this article,which can reduce the consumption of nonreusable resources.Design/methodology/approach-Using tethered UAV to enter the opponent’s UAV cluster and analyze the flow of packets in adversary UAV cluster to find and occupy the central node.The tethered UAV can acquire and analyze key packets by deploying a grayhole attack at the location of the central node,after which the packets are selectively tampered with and discarded to cripple the opposing UAV cluster.Findings-Comparing packet loss rate and delay with a normal network and the network that suffered from grayhole attack,it can be seen that the proposed scheme makes the tethered UAV close to the normal nodes in the UAV cluster and difficult to be detected.In addition,the tethered UAV is able to capture more packets compared to the other two networks,and the average deviation of the tethered UAV in capturing packets is around 5%in repeated experiments.Originality/value-This article proposes an active defense method assisted by tethered UAV,which can minimize the consumption of nonreusable resources.The tethered UAV is converged to ordinary nodes of the opponent’s cluster,in which it is not easily detected.It provides a new direction for point-air defense technology.展开更多
文摘Mobile Ad-hoc Networks(MANET)usage across the globe is increas-ing by the day.Evaluating a node’s trust value has significant advantages since such network applications only run efficiently by involving trustable nodes.The trust values are estimated based on the reputation values of each node in the network by using different mechanisms.However,these mechanisms have various challenging issues which degrade the network performance.Hence,a novel Quality of Service(QoS)Trust Estimation with Black/Gray hole Attack Detection approach is proposed in this research work.Initially,the QoS-based trust estimation is proposed by using a Fuzzy logic scheme.The trust value of each node is estimated by using each node’s reputation values which are deter-mined based on the fuzzy membership function values and utilizing QoS para-meters such as residual energy,bandwidth,node mobility,and reliability.This mechanism prevents only the black hole attack in the network during transmis-sion.But,the gray hole attacks are not identified which in turn increases the pack-et drop rate significantly.Hence,the gray hole attack is also detected based on the Kullback-Leibler(KL)divergence method used for estimating the statistical mea-sures.Additional QoS metrics are considered to prevent the gray hole attack,such as packet loss,packet delivery ratio,and delay for each node.Thus,the proposed mechanism prevents both black hole and gray hole attacks simultaneously.Final-ly,the simulation results show that the effectiveness of the proposed mechanism compared with the other trust-aware routing protocols in MANET.
基金funded by Basic Research Project of the National Defence Science and Industry Bureau(Project No.JCKY2022405C010)the Translational Application Project of the“Wise Eyes Action”(Project No.F2B6A194)Beijing Information Science and Technology University Education Reform(Project No.2024JGYB35).
文摘Purpose-With the development of wireless networks and artificial intelligence technology,unmanned aerial vehicle(UAV)clusters are widely used in various fields and cluster intelligence attacks are more harmful.However,most methods defending against UAV clusters produce consumption of non-reusable resources.To address this problem,a tethered UAV is adopted to perform active defense against adversary UAV clusters in this article,which can reduce the consumption of nonreusable resources.Design/methodology/approach-Using tethered UAV to enter the opponent’s UAV cluster and analyze the flow of packets in adversary UAV cluster to find and occupy the central node.The tethered UAV can acquire and analyze key packets by deploying a grayhole attack at the location of the central node,after which the packets are selectively tampered with and discarded to cripple the opposing UAV cluster.Findings-Comparing packet loss rate and delay with a normal network and the network that suffered from grayhole attack,it can be seen that the proposed scheme makes the tethered UAV close to the normal nodes in the UAV cluster and difficult to be detected.In addition,the tethered UAV is able to capture more packets compared to the other two networks,and the average deviation of the tethered UAV in capturing packets is around 5%in repeated experiments.Originality/value-This article proposes an active defense method assisted by tethered UAV,which can minimize the consumption of nonreusable resources.The tethered UAV is converged to ordinary nodes of the opponent’s cluster,in which it is not easily detected.It provides a new direction for point-air defense technology.
