With the increase in the scale and complexity of offshore wind power systems,zero-dynamics attacks pose a severe threat to the cyber security of such systems.Their concealment makes them difficult to detect using trad...With the increase in the scale and complexity of offshore wind power systems,zero-dynamics attacks pose a severe threat to the cyber security of such systems.Their concealment makes them difficult to detect using traditional output observation-based methods.To address this problem,this paper proposes a zero-dynamics attack detection framework integrating adaptive watermarking and Kalman filtering,which achieves effective attack identification by embedding an adaptive watermark into the system input and conducting residual analysis.Simulation results show that the proposed method can quickly detect zero-dynamics attacks without affecting the normal operation of the system.展开更多
This paper studies the periodic zero-dynamics attacks(ZDAs)in multi-agent systems without velocity measurements under directed graph.Specifically,two types of attack modes are addressed,i.e.,infinite number and finite...This paper studies the periodic zero-dynamics attacks(ZDAs)in multi-agent systems without velocity measurements under directed graph.Specifically,two types of attack modes are addressed,i.e.,infinite number and finite number of zero-dynamics attacks.For the former case,the authors show that the consensus of the considered system cannot be guaranteed.For the latter case,the dynamic evolution of the agents is investigated and it is found that only attacking the rooted agents can destroy the consensus.Then,a sufficient condition which quantifies whether or not the consensus value is destroyed is given,revealing the relationship among parameters of system model,filter and attack signal.Finally,simulations are carried out to verify the effectiveness of the theoretical findings.展开更多
文摘With the increase in the scale and complexity of offshore wind power systems,zero-dynamics attacks pose a severe threat to the cyber security of such systems.Their concealment makes them difficult to detect using traditional output observation-based methods.To address this problem,this paper proposes a zero-dynamics attack detection framework integrating adaptive watermarking and Kalman filtering,which achieves effective attack identification by embedding an adaptive watermark into the system input and conducting residual analysis.Simulation results show that the proposed method can quickly detect zero-dynamics attacks without affecting the normal operation of the system.
基金supported by the National Natural Science Foundation of China under Grant Nos.62173243 and 61933014.
文摘This paper studies the periodic zero-dynamics attacks(ZDAs)in multi-agent systems without velocity measurements under directed graph.Specifically,two types of attack modes are addressed,i.e.,infinite number and finite number of zero-dynamics attacks.For the former case,the authors show that the consensus of the considered system cannot be guaranteed.For the latter case,the dynamic evolution of the agents is investigated and it is found that only attacking the rooted agents can destroy the consensus.Then,a sufficient condition which quantifies whether or not the consensus value is destroyed is given,revealing the relationship among parameters of system model,filter and attack signal.Finally,simulations are carried out to verify the effectiveness of the theoretical findings.
