论文标题
通过减少攻击模型在智能传感器攻击下识别系统漏洞
Identification of System Vulnerability under a Smart Sensor Attack via Attack Model Reduction
论文作者
论文摘要
在这项工作中，我们研究了如何利用模型减少技术来确定可能引起攻击的闭环系统（由工厂和主管组成的闭环系统）的脆弱性。在这里，系统脆弱性是指关键观察序列的存在，这些观察序列可以被特定的智能传感器攻击来造成损害造成的损害。我们考虑了一个非确定的智能攻击，即，在每个收到的观察结果上可能存在多个攻击选择，并采用了我们先前提出的建模框架，其中这种攻击是由标准有限状态自动机捕获的。对于给定的主管s和智能传感器攻击模型A，另一个智能攻击模型A“称为攻击相等的攻击，相当于S，如果由此导致的主管被定义为主管的组成和攻击模型A的组成，则是控制与原始主管的控制相当于S and A. Supportion Surand of Surpisos of Survions of Survions的概念，以使其构成的精神，以使其构成的精神，以使其重新构成，以使其构成的精神，以使其重新定义。综合降低的智能攻击模型A'的攻击相当于S相对于S的攻击，可以转变为经典的主管减少问题，从而使所有现有的合成工具可用于直接适用于我们问题的主管减少。简化且理想的最小国家攻击模型可以揭示所有必要的观察序列，以使攻击者成功，因此，提醒系统设计人员提前采取必要的预防措施，这可能会大大提高系统弹性。举起了一个示例，以显示我们提出的攻击模型减少技术以识别系统漏洞的有效性。
In this work, we investigate how to make use of model reduction techniques to identify the vulnerability of a closed-loop system, consisting of a plant and a supervisor, that might invite attacks. Here, the system vulnerability refers to the existence of key observation sequences that could be exploited by a specific smart sensor attack to cause damage infliction. We consider a nondeterministic smart attack, i.e., there might exist more than one attack choice over each received observation, and adopt our previously proposed modeling framework, where such an attack is captured by a standard finite-state automaton. For a given supervisor S and a smart sensor attack model A, another smart attack model A' is called attack equivalent to A with respect to S, if the resulting compromised supervisor, defined as the composition of the supervisor S and attack model A', is control equivalent to the original compromised supervisor, defined as the composition of S and A. Following the spirit of supervisor reduction that relies on the concept of control congruence, we will show that, this problem of synthesizing a reduced smart attack model A' that is attack equivalent to A with respect to S, can be transformed to a classical supervisor reduction problem, making all existing synthesis tools available for supervisor reduction directly applicable to our problem. A simplified and ideally minimum-state attack model can reveal all necessary observation sequences for the attacker to be successful, thus, reminds system designers to take necessary precautions in advance, which may improve system resilience significantly. An example is presented to show the effectiveness of our proposed attack model reduction technique to identify the system vulnerability.
