Stealthy attacks on Industrial Control Systems can cause significant damage while evading detection. In this paper, instead of focusing on the detection of stealthy attacks, we aim to provide early warnings to operators, in order to avoid physical damage and preserve in advance data that may serve as an evidence during an investigation. We propose a framework to provide grounds for suspicion, i.e. preliminary indicators reflecting the likelihood of success of a stealthy attack. We propose two grounds for suspicion based on the behaviour of the physical process: (i) feasibility of a stealthy attack, and (ii) proximity to unsafe operating regions. We propose a metric to measure grounds for suspicion in real-time and provide soundness principles to ensure that such a metric is consistent with the grounds for suspicion. We apply our framework to Linear Time-Invariant (LTI) systems and formulate the suspicion metric computation as a real-time reachability problem. We validate our framework on a case study involving the benchmark Tennessee-Eastman process. We show through numerical simulation that we can provide early warnings well before a potential stealthy attack can cause damage, while incurring minimal load on the network. Finally, we apply our framework on a use case to illustrate its usefulness in supporting early evidence collection.
翻译:对工业控制系统的隐形攻击在逃避探测的同时可造成重大损害。在本文中,我们不是侧重于探测隐形攻击,而是向操作者提供预警,以避免实际损害,并预先保存可作为调查期间证据的数据。我们提出了一个框架,为怀疑提供依据,即反映隐形攻击成功可能性的初步指标。我们提出了基于物理过程行为的怀疑的两个理由:(一) 隐形攻击的可行性,和(二) 靠近不安全的作业区域。我们提出了一个衡量实时怀疑理由的衡量尺度,并提供健全的原则,以确保这种指标与怀疑理由一致。我们将我们的框架应用于线形时间-内变换系统,并将怀疑参数计算作为实时可达到的问题。我们通过数字模拟,证明我们能够在可能发生的隐形攻击造成损害之前提供早期警告,同时支持网络的早期工作量。最后,我们运用了我们的框架,说明如何使用网络的早期证据。