The increasing reliance on interconnected Internet of Things(IoT)devices has amplified the demand for robust anonymization strategies to protect device identities and ensure secure communication.However,traditional an...The increasing reliance on interconnected Internet of Things(IoT)devices has amplified the demand for robust anonymization strategies to protect device identities and ensure secure communication.However,traditional anonymization methods for IoT networks often rely on static identity models,making them vulnerable to inference attacks through long-term observation.Moreover,these methods tend to sacrifice data availability to protect privacy,limiting their practicality in real-world applications.To overcome these limitations,we propose a dynamic device identity anonymization framework using Moving Target Defense(MTD)principles implemented via Software-Defined Networking(SDN).In our model,the SDN controller periodically reconfigures the network addresses and routes of IoT devices using a constraint-aware backtracking algorithmthat constructs new virtual topologies under connectivity and performance constraints.This address-hopping scheme introduces continuous unpredictability at the network layer dynamically changing device identifiers,routing paths,and even network topology which thwarts attacker reconnaissance while preserving normal communication.Experimental results demonstrate that our approach significantly reduces device identity exposure and scan success rates for attackers compared to static networks.Moreover,the dynamic schememaintains high data availability and network performance.Under attack conditions it reduced average communication delay by approximately 60% vs.an unprotected network,with minimal overhead on system resources.展开更多
Low earth orbit(LEO) satellite communications can provide ubiquitous and reliable services,making it an essential part of the Internet of Everything network. Beam hopping(BH) is an emerging technology for effectively ...Low earth orbit(LEO) satellite communications can provide ubiquitous and reliable services,making it an essential part of the Internet of Everything network. Beam hopping(BH) is an emerging technology for effectively addressing the issue of low resource utilization caused by the non-uniform spatio-temporal distribution of traffic demands. However, how to allocate multi-dimensional resources in a timely and efficient way for the highly dynamic LEO satellite systems remains a challenge. This paper proposes a joint beam scheduling and power optimization beam hopping(JBSPO-BH) algorithm considering the differences in the geographic distribution of sink nodes. The JBSPO-BH algorithm decouples the original problem into two sub-problems. The beam scheduling problem is modelled as a potential game,and the Nash equilibrium(NE) point is obtained as the beam scheduling strategy. Moreover, the penalty function interior point method is applied to optimize the power allocation. Simulation results show that the JBSPO-BH algorithm has low time complexity and fast convergence and achieves better performance both in throughput and fairness. Compared with greedybased BH, greedy-based BH with the power optimization, round-robin BH, Max-SINR BH and satellite resource allocation algorithm, the throughput of the proposed algorithm is improved by 44.99%, 20.79%,156.06%, 15.39% and 8.17%, respectively.展开更多
基金supported by the National Key Research and Development Program of China(Project No.2022YFB3104300).
文摘The increasing reliance on interconnected Internet of Things(IoT)devices has amplified the demand for robust anonymization strategies to protect device identities and ensure secure communication.However,traditional anonymization methods for IoT networks often rely on static identity models,making them vulnerable to inference attacks through long-term observation.Moreover,these methods tend to sacrifice data availability to protect privacy,limiting their practicality in real-world applications.To overcome these limitations,we propose a dynamic device identity anonymization framework using Moving Target Defense(MTD)principles implemented via Software-Defined Networking(SDN).In our model,the SDN controller periodically reconfigures the network addresses and routes of IoT devices using a constraint-aware backtracking algorithmthat constructs new virtual topologies under connectivity and performance constraints.This address-hopping scheme introduces continuous unpredictability at the network layer dynamically changing device identifiers,routing paths,and even network topology which thwarts attacker reconnaissance while preserving normal communication.Experimental results demonstrate that our approach significantly reduces device identity exposure and scan success rates for attackers compared to static networks.Moreover,the dynamic schememaintains high data availability and network performance.Under attack conditions it reduced average communication delay by approximately 60% vs.an unprotected network,with minimal overhead on system resources.
文摘针对无线传感网络中传统DV-Hop(Distance Vector Hop)定位算法节点分布不均匀导致定位误差较大的问题,提出了非均匀网络中半径可调的ARDV-Hop(Adjustable Radius DV-Hop in Non-uniform Networks)定位算法。该算法通过半径可调的方式对节点间的跳数进行细化,用细化后呈小数级的跳数代替传统的整数级跳数,并建立了数据能量消耗模型,优化了网络传输性能。ARDV-Hop算法还针对节点分布不均匀的区域提出跳距优化算法:在节点密度大的区域,采用余弦定理优化跳距;密度小的区域,采用最小均方误差(Least Mean Square,LMS)来修正跳距。仿真实验表明,在同等网络环境下,与传统DV-Hop算法、GDV-Hop算法和WOA-DV-Hop算法相比,ARDV-Hop算法能更有效地降低定位误差.
基金supported by the National Key Research and Development Program of China 2021YFB2900504, 2020YFB1807900。
文摘Low earth orbit(LEO) satellite communications can provide ubiquitous and reliable services,making it an essential part of the Internet of Everything network. Beam hopping(BH) is an emerging technology for effectively addressing the issue of low resource utilization caused by the non-uniform spatio-temporal distribution of traffic demands. However, how to allocate multi-dimensional resources in a timely and efficient way for the highly dynamic LEO satellite systems remains a challenge. This paper proposes a joint beam scheduling and power optimization beam hopping(JBSPO-BH) algorithm considering the differences in the geographic distribution of sink nodes. The JBSPO-BH algorithm decouples the original problem into two sub-problems. The beam scheduling problem is modelled as a potential game,and the Nash equilibrium(NE) point is obtained as the beam scheduling strategy. Moreover, the penalty function interior point method is applied to optimize the power allocation. Simulation results show that the JBSPO-BH algorithm has low time complexity and fast convergence and achieves better performance both in throughput and fairness. Compared with greedybased BH, greedy-based BH with the power optimization, round-robin BH, Max-SINR BH and satellite resource allocation algorithm, the throughput of the proposed algorithm is improved by 44.99%, 20.79%,156.06%, 15.39% and 8.17%, respectively.
