Pole-Dynamics Attacks Detection in Multiagent Systems by Distributed Additive Watermarking
研究了多智能体系统中隐蔽的分布式极点动力学攻击的检测问题，提出分布式加性水印方法，通过差异化水印协方差隔离被攻击链路，并量化了检测性能与水印的关系。
This article investigates the stealthy distributed pole-dynamics attacks (dPDAs) detection for multiagent systems (MASs) by distributed additive watermarking (DAW). First, the limitation of traditional MASs for dPDAs is revealed, where dPDAs cannot be detected. Second, unlike the well-established single-agent additive watermarking, to eliminate the side effect of watermarking signal on system state and enable dPDAs detection, the proposed DAW adds watermarking to the control signal of any agent for transmission and removes watermarking of the control signal after receiving it. Meanwhile, the covariance of the watermarking signal in DAW for all agents is different from each other to enable compromised links isolation. Furthermore, the relationship between the dPDAs detection performance and DAW is quantified in the sense of expectation, where the dPDAs detection performance is directly proportional to the sum of the watermarking covariance of the compromised links. Third, leveraging the relationship between dPDAs detection performance and DAW, a DAW-based link isolation scheme is proposed to accurately isolate the compromised links by comparing with the detection function and its approximation, where the approximation of the detection function is iteratively calculated on all possible attack links combination for the compromised agent. As a result, the adverse impacts of dPDAs on MASs are mitigated. Finally, simulation results are conducted to validate the theoretical results.