Cyber–Physical Systems (CPSs) refer to control systems which are composed of sensors, actuators, computers and network components. These systems are vulnerable to unforeseen failures and external malicious attacks. In this paper, we analyze the stability of CPSs under stochastic deception attacks. To this end: (i) we propose a statistical Intrusion Detection System (IDS) for detection of deception attacks in CPSs; (ii) identify the place of such attacks by taking advantage of a novel cryptographic adversarial model; (iii) based on the real-time data and characterizing the deception attacks by IDS, we analyze the effect of both adaptive and blind/random types of deception attacks on the stability of CPSs. We do this through Markov chain modeling and subsequently extract the sufficient stability conditions. (iv) as an extra effort, introduce a new adaptive and intelligent deception attack. We validate our findings by illustrative examples at the end of the paper. Our results show that proposed IDS can detect deception attacks with low false positive and negative rates in real time. The results also confirm the validity of the theoretically-predicted stability conditions.

中文翻译：

---

网络物理系统随机欺骗攻击的识别和分析

信息物理系统（CPS）是指由传感器、执行器、计算机和网络组件组成的控制系统。这些系统很容易受到不可预见的故障和外部恶意攻击的影响。在本文中，我们分析了随机欺骗攻击下 CPS 的稳定性。为此：（i）我们提出了一种统计入侵检测系统（IDS）来检测 CPS 中的欺骗攻击； (ii) 利用新颖的密码对抗模型来识别此类攻击的地点； (iii)基于实时数据并描述IDS欺骗攻击的特征，我们分析了自适应和盲目/随机类型的欺骗攻击对CPS稳定性的影响。我们通过马尔可夫链建模来做到这一点，并随后提取足够的稳定性条件。 (iv) 作为额外的努力，引入一种新的自适应和智能欺骗攻击。我们通过本文末尾的说明性示例验证了我们的发现。我们的结果表明，所提出的 IDS 可以实时检测欺骗攻击，误报率和漏报率都很低。结果还证实了理论预测的稳定性条件的有效性。