Adaptive window-based sensor attack detection for cyber-physical systems
Adaptive window-based sensor attack detection for cyber-physical systems
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DOI：
10.1145/3489517.3530555
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
Lin Zhang;Zifan Wang;Mengyu Liu;Fanxin Kong
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文献类型：
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作者：
Lin Zhang;Zifan Wang;Mengyu Liu;Fanxin Kong
传感器攻击改变传感器读数并欺骗网络物理系统（CPS）执行危险操作。现有的检测工作倾向于同时最小化检测延迟和假警报，而这两个指标之间存在明显的权衡。相反，我们认为攻击检测应该在物理系统处于不同状态时动态平衡这两个度量。根据这一论点，我们提出了一个自适应传感器攻击检测系统，该系统由三个组件组成-自适应检测器，检测截止日期估计器和数据记录器。它可以在运行时调整检测延迟和假警报，以满足不同的检测截止日期并提高可用性（或假警报）。最后，我们实现了我们的检测系统，并使用多个CPS模拟器和一个缩小规模的自动驾驶汽车试验台对其进行了验证。
Sensor attacks alter sensor readings and spoof Cyber-Physical Systems (CPS) to perform dangerous actions. Existing detection works tend to minimize the detection delay and false alarms at the same time, while there is a clear trade-off between the two metrics. Instead, we argue that attack detection should dynamically balance the two metrics when a physical system is at different states. Along with this argument, we propose an adaptive sensor attack detection system that consists of three components - an adaptive detector, detection deadline estimator, and data logger. It can adapt the detection delay and thus false alarms at run time to meet a varying detection deadline and improve usability (or false alarms). Finally, we implement our detection system and validate it using multiple CPS simulators and a reduced-scale autonomous vehicle testbed.