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Probabilistic verification of attack detection using logical observer ?

机译：使用逻辑观察者的攻击检测的概率验证 ？

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摘要

This paper focuses on the detection of cyber-attacks in a timed probabilistic setting. The plant and the possible attacks are described in terms of a labeled continuous time Markov model that includes both observable and unobservable events, and where each attack corresponds to a particular subset of states. Consequently, attack detection is reformulated as a state estimation problem. A verification methodology is described using a parallel-like composition of the Markov model and its logical observer. The construction of this parallel composition allows us to (i) concisely characterize the set of attacks that can be detected based on the sequences of observations they generate, and (ii) compute performance indicators of interest, such as the a priori probability of an undetectable attack, the average detectability, and the mean delay to detection.
机译：本文侧重于在定时概率设置中检测网络攻击。植物和可能的攻击是根据标记的连续时间马尔可夫模型描述的，该模型包括可观察和不可观察的事件，并且每个攻击对应于特定状态子集的位置。因此，攻击检测被重新重新重新重整为状态估计问题。使用Markov模型的并行形式及其逻辑观测器描述验证方法。该并联组合的构造允许我们（i）简明地表征可以基于它们产生的观察序列来检测的一组攻击，以及（ii）计算性能指标，例如未检测到的优先概率攻击，平均可检测性和平均延迟检测。

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