The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-inpu...The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-input multiple-output(MIMO)communication system with a STAR-RIS,a base station(BS),an eavesdropper,and multiple users,the system security rate is studied.A joint design of the power allocation at the transmitter and phase shift matrices for reflection and transmission at the STAR-RIS is conducted,in order to maximize the worst achievable security data rate(ASDR).Since the problem is nonconvex and hence challenging,a particle swarm optimization(PSO)based algorithm is developed to tackle the problem.Both the cases of continuous and discrete phase shift matrices at the STAR-RIS are considered.Simulation results demonstrate the effectiveness of the proposed algorithm and shows the benefits of using STAR-RIS in MIMO mutliuser systems.展开更多
Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems...Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems are susceptible to malicious eavesdropping attacks during the information transmission,and this issue has not been adequately addressed.In this paper,we propose a physical-layer secure fog computing IoT system model,which is able to improve the physical layer security of fog computing IoT networks against the malicious eavesdropping of multiple eavesdroppers.The secrecy rate of the proposed model is analyzed,and the quantum galaxy–based search algorithm(QGSA)is proposed to solve the hybrid task scheduling and resource management problem of the network.The computational complexity and convergence of the proposed algorithm are analyzed.Simulation results validate the efficiency of the proposed model and reveal the influence of various environmental parameters on fog computing IoT networks.Moreover,the simulation results demonstrate that the proposed hybrid task scheduling and resource management scheme can effectively enhance secrecy performance across different communication scenarios.展开更多
A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with t...A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with the UAV network,we first consider both achievable secrecy rate maximization and total transmit power minimization,and formulate a multi-objective optimization problem(MOOP)using the weighted Tchebycheff approach.Then,by supposing that only imperfect channel state information based on the angular information is available,we propose a method combining angular discretization with Taylor approximation to transform the non-convex objective function and constraints to the convex ones.Next,we adopt semi-definite programming together with randomization technology to solve the original MOOP and obtain the BF weight vector.Finally,simulation results illustrate that the Pareto optimal trade-off can be achieved,and the superiority of our proposed scheme is confirmed by comparing with the existing BF schemes.展开更多
Communication security is a critical aspect of QoS provisioning in wireless mesh network （WMN）. Because of the inherent characteristics of WMN, conventional security mechanisms cannot be applied. In order to guarant...Communication security is a critical aspect of QoS provisioning in wireless mesh network （WMN）. Because of the inherent characteristics of WMN, conventional security mechanisms cannot be applied. In order to guarantee the communication security, a novel communication security mechanism is proposed. The mechanism uses a communication encryption scheme to encrypt data packets and employs a risk avoidance scheme to avoid the malicious nodes during communications. Simulation results indicate that the mechanism is able to provide secure communication effectively and reduce the damage of attacks through multiple paths.展开更多
We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reco...We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.展开更多
Post-quantum transport layer security(PQ-TLS)is capable of effectively defending against quantum threats to current network communications,whereas its larger public key and certificate sizes as well as higher computat...Post-quantum transport layer security(PQ-TLS)is capable of effectively defending against quantum threats to current network communications,whereas its larger public key and certificate sizes as well as higher computational overhead may result in a significant performance reduction compared with conventional TLS.In this paper,we present a systematic evaluation of PQ-TLS performance across diverse deployment scenarios to address the following critical research questions.(1)What is the performance behavior of PQ-TLS across different TLS modes?(2)How does PQ-TLS perform across varying client scales?(3)Which network topology is most suitable for PQ-TLS?(4)How does PQ-TLS perform on personal computers(PCs)compared to embedded IoT devices?To the best of our knowledge,this is the first work to comprehensively address these issues,offering implementers some insights into PQ-TLS performance and guidance for optimizing it across diverse scenarios.展开更多
网络空间安全防御全国重点实验室两篇模型安全研究成果被USENIX Security 2026录用近日,网络空间安全防御全国重点实验室古晓艳团队和张锐团队分别在人工智能模型安全管理与隐私保护方面取得了阶段性进展。博士研究生商卓逸在刘延伟副...网络空间安全防御全国重点实验室两篇模型安全研究成果被USENIX Security 2026录用近日,网络空间安全防御全国重点实验室古晓艳团队和张锐团队分别在人工智能模型安全管理与隐私保护方面取得了阶段性进展。博士研究生商卓逸在刘延伟副研究员、古晓艳正高级工程师、王伟平研究员指导下完成的论文“Attesting Model Lineage by Consisted Knowledge Evolution with Fine-Tuning Trajectory”,博士研究生吕韵律在张锐研究员指导下完成的论文“SMASH:Scalable Maliciously Secure Hybrid Multi-Party Computation Framework for Privacy-Preserving Large Language Models”,均被第35届USENIX Security Symposium录用。USENIX Security是全球信息与系统安全领域的国际学术会议之一,与IEEE S&P、ACM CCS和NDSS并称为网络安全领域的“四大会议”,均被中国计算机学会(CCF)列为A类会议。展开更多
Multi-domain competition is developing for disintegrating the component of the opponent’s operational system and winning advantage in decision space.Island air defense is a typical multi-domain security problem,which...Multi-domain competition is developing for disintegrating the component of the opponent’s operational system and winning advantage in decision space.Island air defense is a typical multi-domain security problem,which dramatically increases the complexity of decision-making by considering different factors such as multi-stages decisions,multi-domain settings,imperfection information,and uncertain events.However,current research on island air defense security problems is sparse and lacks consideration of key factors.To provide support for assisting human commanders to take wise decisions in a complex environment,we build a multi-domain multi-state island air defense model and propose responding solving algorithms.We study the whole progress of island air defense and propose a multi-domain,multi-stage imperfection information security game that formulates critical characters in the adversarial scenario of island air defense.In addition,considering a bounded rational opponent’s possible strategies,we propose an opponent-aware Monte Carlo counterfactual regret minimization algorithm for learning a robust defensive strategy in the security game.We evaluate our methods in various adversarial scenarios.The results show that our equilibrium learning method can effectively play against an opponent with bounded rationality and significantly outperform some advanced algorithms.展开更多
The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced met...The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced metering infrastructure services.However,this digital transformation also exposes power system to evolving threats,ranging from cyber intrusions and electricity theft to device malfunctions,and the unpredictable nature of these anomalies,coupled with the scarcity of labeled fault data,makes realtime detection exceptionally challenging.To address these difficulties,a real-time decision support framework is presented for smart meter anomality detection that leverages rolling time windows and two self-supervised contrastive learning modules.The first module synthesizes diverse negative samples to overcome the lack of labeled anomalies,while the second captures intrinsic temporal patterns for enhanced contextual discrimination.The end-to-end framework continuously updates its model with rolling updated meter data to deliver timely identification of emerging abnormal behaviors in evolving grids.Extensive evaluations on eight publicly available smart meter datasets over seven diverse abnormal patterns testing demonstrate the effectiveness of the proposed full framework,achieving average recall and F1 score of more than 0.85.展开更多
文摘The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-input multiple-output(MIMO)communication system with a STAR-RIS,a base station(BS),an eavesdropper,and multiple users,the system security rate is studied.A joint design of the power allocation at the transmitter and phase shift matrices for reflection and transmission at the STAR-RIS is conducted,in order to maximize the worst achievable security data rate(ASDR).Since the problem is nonconvex and hence challenging,a particle swarm optimization(PSO)based algorithm is developed to tackle the problem.Both the cases of continuous and discrete phase shift matrices at the STAR-RIS are considered.Simulation results demonstrate the effectiveness of the proposed algorithm and shows the benefits of using STAR-RIS in MIMO mutliuser systems.
基金supported by the National Natural Science Foundation of China(61571149,62001139)the Initiation Fund for Postdoctoral Research in Heilongjiang Province(LBH-Q19098)the Natural Science Foundation of Heilongjiang Province(LH2020F0178).
文摘Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems are susceptible to malicious eavesdropping attacks during the information transmission,and this issue has not been adequately addressed.In this paper,we propose a physical-layer secure fog computing IoT system model,which is able to improve the physical layer security of fog computing IoT networks against the malicious eavesdropping of multiple eavesdroppers.The secrecy rate of the proposed model is analyzed,and the quantum galaxy–based search algorithm(QGSA)is proposed to solve the hybrid task scheduling and resource management problem of the network.The computational complexity and convergence of the proposed algorithm are analyzed.Simulation results validate the efficiency of the proposed model and reveal the influence of various environmental parameters on fog computing IoT networks.Moreover,the simulation results demonstrate that the proposed hybrid task scheduling and resource management scheme can effectively enhance secrecy performance across different communication scenarios.
基金supported by the Key International Cooperation Research Project(61720106003)the National Natural Science Foundation of China(62001517)+2 种基金the Shanghai Aerospace Science and Technology Innovation Foundation(SAST2019-095)the NUPTSF(NY220111)the Foundational Research Project of Complex Electronic System Simulation Laboratory(DXZT-JC-ZZ-2019-009,DXZTJC-ZZ-2019-005).
文摘A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with the UAV network,we first consider both achievable secrecy rate maximization and total transmit power minimization,and formulate a multi-objective optimization problem(MOOP)using the weighted Tchebycheff approach.Then,by supposing that only imperfect channel state information based on the angular information is available,we propose a method combining angular discretization with Taylor approximation to transform the non-convex objective function and constraints to the convex ones.Next,we adopt semi-definite programming together with randomization technology to solve the original MOOP and obtain the BF weight vector.Finally,simulation results illustrate that the Pareto optimal trade-off can be achieved,and the superiority of our proposed scheme is confirmed by comparing with the existing BF schemes.
基金This project was supported by the National Natural Science Foundation of China (60573129).
文摘Communication security is a critical aspect of QoS provisioning in wireless mesh network （WMN）. Because of the inherent characteristics of WMN, conventional security mechanisms cannot be applied. In order to guarantee the communication security, a novel communication security mechanism is proposed. The mechanism uses a communication encryption scheme to encrypt data packets and employs a risk avoidance scheme to avoid the malicious nodes during communications. Simulation results indicate that the mechanism is able to provide secure communication effectively and reduce the damage of attacks through multiple paths.
基金funding from the Australian Government,via grant AUSMURIB000001 associated with ONR MURI Grant N00014-19-1-2571。
文摘We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.
基金Special Fund for Key Technologies in Blockchain of Shanghai Scientific and Technological Committee(23511100300)。
文摘Post-quantum transport layer security(PQ-TLS)is capable of effectively defending against quantum threats to current network communications,whereas its larger public key and certificate sizes as well as higher computational overhead may result in a significant performance reduction compared with conventional TLS.In this paper,we present a systematic evaluation of PQ-TLS performance across diverse deployment scenarios to address the following critical research questions.(1)What is the performance behavior of PQ-TLS across different TLS modes?(2)How does PQ-TLS perform across varying client scales?(3)Which network topology is most suitable for PQ-TLS?(4)How does PQ-TLS perform on personal computers(PCs)compared to embedded IoT devices?To the best of our knowledge,this is the first work to comprehensively address these issues,offering implementers some insights into PQ-TLS performance and guidance for optimizing it across diverse scenarios.
文摘网络空间安全防御全国重点实验室两篇模型安全研究成果被USENIX Security 2026录用近日,网络空间安全防御全国重点实验室古晓艳团队和张锐团队分别在人工智能模型安全管理与隐私保护方面取得了阶段性进展。博士研究生商卓逸在刘延伟副研究员、古晓艳正高级工程师、王伟平研究员指导下完成的论文“Attesting Model Lineage by Consisted Knowledge Evolution with Fine-Tuning Trajectory”,博士研究生吕韵律在张锐研究员指导下完成的论文“SMASH:Scalable Maliciously Secure Hybrid Multi-Party Computation Framework for Privacy-Preserving Large Language Models”,均被第35届USENIX Security Symposium录用。USENIX Security是全球信息与系统安全领域的国际学术会议之一,与IEEE S&P、ACM CCS和NDSS并称为网络安全领域的“四大会议”,均被中国计算机学会(CCF)列为A类会议。
基金supported by the National Natural Science Foundation of China(92271108,61702528,61806212,62173336).
文摘Multi-domain competition is developing for disintegrating the component of the opponent’s operational system and winning advantage in decision space.Island air defense is a typical multi-domain security problem,which dramatically increases the complexity of decision-making by considering different factors such as multi-stages decisions,multi-domain settings,imperfection information,and uncertain events.However,current research on island air defense security problems is sparse and lacks consideration of key factors.To provide support for assisting human commanders to take wise decisions in a complex environment,we build a multi-domain multi-state island air defense model and propose responding solving algorithms.We study the whole progress of island air defense and propose a multi-domain,multi-stage imperfection information security game that formulates critical characters in the adversarial scenario of island air defense.In addition,considering a bounded rational opponent’s possible strategies,we propose an opponent-aware Monte Carlo counterfactual regret minimization algorithm for learning a robust defensive strategy in the security game.We evaluate our methods in various adversarial scenarios.The results show that our equilibrium learning method can effectively play against an opponent with bounded rationality and significantly outperform some advanced algorithms.
文摘The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced metering infrastructure services.However,this digital transformation also exposes power system to evolving threats,ranging from cyber intrusions and electricity theft to device malfunctions,and the unpredictable nature of these anomalies,coupled with the scarcity of labeled fault data,makes realtime detection exceptionally challenging.To address these difficulties,a real-time decision support framework is presented for smart meter anomality detection that leverages rolling time windows and two self-supervised contrastive learning modules.The first module synthesizes diverse negative samples to overcome the lack of labeled anomalies,while the second captures intrinsic temporal patterns for enhanced contextual discrimination.The end-to-end framework continuously updates its model with rolling updated meter data to deliver timely identification of emerging abnormal behaviors in evolving grids.Extensive evaluations on eight publicly available smart meter datasets over seven diverse abnormal patterns testing demonstrate the effectiveness of the proposed full framework,achieving average recall and F1 score of more than 0.85.
文摘近日,武汉大学国家网络安全学院2023级硕士研究生闫楠作为第一作者撰写的论文被第34届USENIX安全研讨会(The34th USENIX Security Symposium 2025)录用。论文题目为“Embed X:Embedding-Based Cross-Trigger Backdoor Attack Against Large Language Models”(《Embed X:基于嵌入的跨触发器大语言模型后门攻击》),指导老师为国家网络安全学院副研究员李雨晴(通信作者)、教授陈晶(通信作者)、副教授何琨。华中科技大学副教授王雄、香港科技大学教授李波参与合作。
