A prediction-aided routing algorithm based on ant colony optimization mode （PRACO） to achieve energy-aware data-gathering routing structure in wireless sensor networks （WSN） is presented. We adopt autoregressive m...A prediction-aided routing algorithm based on ant colony optimization mode （PRACO） to achieve energy-aware data-gathering routing structure in wireless sensor networks （WSN） is presented. We adopt autoregressive moving average model （ARMA） to predict dynamic tendency in data traffic and deduce the construction of load factor, which can help to reveal the future energy status of sensor in WSN. By checking the load factor in heuristic factor and guided by novel pheromone updating rule, multi-agent, i. e. , artificial ants, can adaptively foresee the local energy state of networks and the corresponding actions could be taken to enhance the energy efficiency in routing construction. Compared with some classic energy-saving routing schemes, the simulation results show that the proposed routing building scheme can ① effectively reinforce the robustness of routing structure by mining the temporal associability and introducing multi-agent optimization to balance the total energy cost for data transmission, ② minimize the total communication consumption, and ③prolong the lifetime of networks.展开更多
Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harm...Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harmful attacks. Routing randomization is a relevant research direction for moving target defense, which has been proven to be an effective method to resist eavesdropping attacks. To counter eavesdropping attacks, in this study, we analyzed the existing routing randomization methods and found that their security and usability need to be further improved. According to the characteristics of eavesdropping attacks, which are “latent and transferable”, a routing randomization defense method based on deep reinforcement learning is proposed. The proposed method realizes routing randomization on packet-level granularity using programmable switches. To improve the security and quality of service of legitimate services in networks, we use the deep deterministic policy gradient to generate random routing schemes with support from powerful network state awareness. In-band network telemetry provides real-time, accurate, and comprehensive network state awareness for the proposed method. Various experiments show that compared with other typical routing randomization defense methods, the proposed method has obvious advantages in security and usability against eavesdropping attacks.展开更多
As an emerging network paradigm,the software-defined network(SDN)finds extensive application in areas such as smart grids,the Internet of Things(IoT),and edge computing.The forwarding layer in software-defined network...As an emerging network paradigm,the software-defined network(SDN)finds extensive application in areas such as smart grids,the Internet of Things(IoT),and edge computing.The forwarding layer in software-defined networks is susceptible to eavesdropping attacks.Route hopping is amoving target defense(MTD)technology that is frequently employed to resist eavesdropping attacks.In the traditional route hopping technology,both request and reply packets use the same hopping path.If an eavesdropping attacker monitors the nodes along this path,the risk of 100%data leakage becomes substantial.In this paper,we present an effective route hopping approach,called two-day different path(TDP),that turns communication paths into untraceable moving targets.This technology minimizes the probability of data leakage by transmitting request data and reply data through different paths.Firstly,a brief introduction to the network model and attack model involved in this paper is given.Secondly,the algorithm and processingmethod of the TDP are proposed.Thirdly,the paper proposes three differentmetrics tomeasure the effectiveness of the proposed approach.Finally,theoretical analysis and simulation results show that the TDP can effectively reduce the percentage of data exposure,decrease eavesdropping attack success probability,and improve the unpredictability of the path.展开更多
In marine wireless sensor networks(MWSNs),an appropriate routing protocol is the key to the collaborative collection and efficient transmission of massive data.However,designing an appropriate routing protocol under t...In marine wireless sensor networks(MWSNs),an appropriate routing protocol is the key to the collaborative collection and efficient transmission of massive data.However,designing an appropriate routing protocol under the condition of sparse marine node deployment,highly dynamic network topology,and limited node energy is complicated.Moreover,the absence of continuous endto-end connection introduces further difficulties in the design of routing protocols.In this case,we present a novel energy-efficient opportunistic routing(Novel Energy-Efficient Opportunistic Routing,NEOR)protocol for MWSNs that is based on compressed sensing and power control.First,a lightweight time-series prediction method-weighted moving average method is proposed to predict the packet advancement value such that the number of location information that is exchanged among a node and its neighbor nodes can be minimized.Second,an adaptive power control mechanism is presented to determine the optimal transmitting power and candidate nodeset on the basis of node mobility,packet advancement,communication link quality,and remaining node energy.Subsequently,a timer-based scheduling algorithm is utilized to coordinate packet forwarding to avoid packet conflict.Furthermore,we introduce the compressed sensing theory to compress perceptual data at source nodes and reconstruct the original data at sink nodes.Therefore,energy consumption in the MWSNs is greatly reduced due to the decrease in the amount of data perception and transmission.Numerical simulation experiments are carried out in a wide range of marine scenarios to verify the superiority of our approach over selected benchmark algorithms.展开更多
Ad Hoc网络的移动特性是安全路由中不能忽略的一个重要因素.在一个频繁变化甚至高速移动的网络中,目前大部分安全路由协议难以完成可信通信方的认证,从而无法建立起安全的路由通道.这是由于认证过程是一个连续的消息交互过程,移动特性...Ad Hoc网络的移动特性是安全路由中不能忽略的一个重要因素.在一个频繁变化甚至高速移动的网络中,目前大部分安全路由协议难以完成可信通信方的认证,从而无法建立起安全的路由通道.这是由于认证过程是一个连续的消息交互过程,移动特性使得这个连续交互无法保证.文中在链路状态路由协议OLSR的基础上提出了基于信任保留的安全路由协议TPSRP,该协议采用信任保留的方式对节点进行认证,解决高速移动网络中节点认证问题.TPSRP还针对目前信任评估方法缺少有效的自适应性提出了一种新的信任评估手段,使得节点可以通过综合的信任信息,自我辨别并限制内部背叛节点的恶意行为,同时有效地检测与抵抗Ad Hoc网络中的协作攻击,如虫洞攻击等.最后的仿真显示,在网络移动特性增强的情况下,TPSRP的认证性能要优于传统认证协议,并能够有效孤立攻击节点.展开更多
基金Supported by the National Natural Science Foundation of China(60802005,60965002,50803016)Science Foundation forthe Excellent Youth Scholars at East China University of Science and Technology(YH0157127)Undergraduate Innovational Experimentation Program in ECUST(X1033)
文摘A prediction-aided routing algorithm based on ant colony optimization mode （PRACO） to achieve energy-aware data-gathering routing structure in wireless sensor networks （WSN） is presented. We adopt autoregressive moving average model （ARMA） to predict dynamic tendency in data traffic and deduce the construction of load factor, which can help to reveal the future energy status of sensor in WSN. By checking the load factor in heuristic factor and guided by novel pheromone updating rule, multi-agent, i. e. , artificial ants, can adaptively foresee the local energy state of networks and the corresponding actions could be taken to enhance the energy efficiency in routing construction. Compared with some classic energy-saving routing schemes, the simulation results show that the proposed routing building scheme can ① effectively reinforce the robustness of routing structure by mining the temporal associability and introducing multi-agent optimization to balance the total energy cost for data transmission, ② minimize the total communication consumption, and ③prolong the lifetime of networks.
文摘Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harmful attacks. Routing randomization is a relevant research direction for moving target defense, which has been proven to be an effective method to resist eavesdropping attacks. To counter eavesdropping attacks, in this study, we analyzed the existing routing randomization methods and found that their security and usability need to be further improved. According to the characteristics of eavesdropping attacks, which are “latent and transferable”, a routing randomization defense method based on deep reinforcement learning is proposed. The proposed method realizes routing randomization on packet-level granularity using programmable switches. To improve the security and quality of service of legitimate services in networks, we use the deep deterministic policy gradient to generate random routing schemes with support from powerful network state awareness. In-band network telemetry provides real-time, accurate, and comprehensive network state awareness for the proposed method. Various experiments show that compared with other typical routing randomization defense methods, the proposed method has obvious advantages in security and usability against eavesdropping attacks.
基金the Natural Science Foundation of Guangdong Province under Grant Number 2021A1515011910by the Shenzhen Science and Technology Program under Grant No.KQTD20190929172704911。
文摘As an emerging network paradigm,the software-defined network(SDN)finds extensive application in areas such as smart grids,the Internet of Things(IoT),and edge computing.The forwarding layer in software-defined networks is susceptible to eavesdropping attacks.Route hopping is amoving target defense(MTD)technology that is frequently employed to resist eavesdropping attacks.In the traditional route hopping technology,both request and reply packets use the same hopping path.If an eavesdropping attacker monitors the nodes along this path,the risk of 100%data leakage becomes substantial.In this paper,we present an effective route hopping approach,called two-day different path(TDP),that turns communication paths into untraceable moving targets.This technology minimizes the probability of data leakage by transmitting request data and reply data through different paths.Firstly,a brief introduction to the network model and attack model involved in this paper is given.Secondly,the algorithm and processingmethod of the TDP are proposed.Thirdly,the paper proposes three differentmetrics tomeasure the effectiveness of the proposed approach.Finally,theoretical analysis and simulation results show that the TDP can effectively reduce the percentage of data exposure,decrease eavesdropping attack success probability,and improve the unpredictability of the path.
基金supported by the National Natural Science Foundation of China(Nos.52201403,52201401,52071200,52102397,61701299,51709167)the National Key Research and Development Program(No.2021YFC2801002)+4 种基金the China Postdoctoral Science Foundation(Nos.2021M 700790,2022M712027)the Fund of National Engineering Research Center for Water Transport Safety(No.A2022003)the Foundation for Jiangsu Key Laboratory of Traffic and Transportation Security(No.TTS2021-05)the Fund of Hubei Key Laboratory of Inland Shipping Technology(No.NHHY2021002)the Top-Notch Innovative Program for Postgraduates of Shanghai Maritime University(Nos.2019YBR006,2019YBR002).
文摘In marine wireless sensor networks(MWSNs),an appropriate routing protocol is the key to the collaborative collection and efficient transmission of massive data.However,designing an appropriate routing protocol under the condition of sparse marine node deployment,highly dynamic network topology,and limited node energy is complicated.Moreover,the absence of continuous endto-end connection introduces further difficulties in the design of routing protocols.In this case,we present a novel energy-efficient opportunistic routing(Novel Energy-Efficient Opportunistic Routing,NEOR)protocol for MWSNs that is based on compressed sensing and power control.First,a lightweight time-series prediction method-weighted moving average method is proposed to predict the packet advancement value such that the number of location information that is exchanged among a node and its neighbor nodes can be minimized.Second,an adaptive power control mechanism is presented to determine the optimal transmitting power and candidate nodeset on the basis of node mobility,packet advancement,communication link quality,and remaining node energy.Subsequently,a timer-based scheduling algorithm is utilized to coordinate packet forwarding to avoid packet conflict.Furthermore,we introduce the compressed sensing theory to compress perceptual data at source nodes and reconstruct the original data at sink nodes.Therefore,energy consumption in the MWSNs is greatly reduced due to the decrease in the amount of data perception and transmission.Numerical simulation experiments are carried out in a wide range of marine scenarios to verify the superiority of our approach over selected benchmark algorithms.
