Characterization of a CUSUM model-based sensor attack detector
Characterization of a CUSUM model-based sensor attack detector
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DOI：
10.1109/cdc.2016.7798446
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发表时间：
2016-12
期刊：
影响因子：
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通讯作者：
C. Murguia;Justin Ruths
中科院分区：
文献类型：
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作者：
C. Murguia;Justin Ruths
在线性时不变网络物理系统的传感器攻击背景下，我们提出了一种基于模型的累积和（CUSUM）程序来识别伪造的传感器测量。在给定系统动力学、控制和估计方案以及噪声统计的情况下，为了实现期望的检测性能，我们导出了用于设计和调整CUSUM程序的工具。我们描述了隐身攻击者在未被检测过程检测到的情况下对系统造成的状态退化。此外，我们量化了使用动态检测器（CUSUM）的优势，它利用状态的历史，而静态检测器（Bad-Data）一次使用单个测量。仿真实验验证了该检测方案的性能。
In the context of sensor attacks on linear time-invariant cyber-physical systems, we propose a model-based cumulative sum (CUSUM) procedure for identifying falsified sensor measurements. To fulfill a desired detection performance-given the system dynamics, control and estimation schemes, and noise statistics-we derive tools for designing and tuning the CUSUM procedure. We characterize the state degradation that a stealthy attacker can induce to the system while remaining undetected by the detection procedure. Moreover, we quantify the advantage of using a dynamic detector (CUSUM), which leverages the history of the state, over a static detector (Bad-Data) which uses a single measurement at a time. Simulation experiments are presented to illustrate the performance of the detection scheme.