Diagnosability Verification and Enforcement in Labeled Petri Nets Under Sensor Attacks

IF 8.6 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Shaopeng Hu;Zhiwu Li;Ding Liu
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引用次数: 0

Abstract

This article formalizes and solves the problems of diagnosability verification and enforcement in discrete event systems modeled with labeled Petri nets (LPNs) under sensor attacks. Given a plant, attackers work as a group in the framework of a coordinated distributed architecture and have the ability to edit some sensor readings to conceal the faults to confuse the operator. Furthermore, attackers necessarily remain furtive, i.e., their presence should not be discovered by the operator. In order to describe the set of all possible furtive attacks, a joint furtive diagnoser is established. We prove that an LPN under the above attacks is diagnosable if and only if its joint furtive diagnoser does not have the cycles composed of pairs of either faulty states and normal states, or faulty states and uncertain states. A new labeling function is proposed to enforce a plant to be diagnosable against as many attacks as possible. Examples are provided to illustrate the proposed method.
传感器攻击下标签 Petri 网的可诊断性验证与执行
本文形式化并解决了在传感器攻击下用标记Petri网(lpn)建模的离散事件系统的可诊断性验证和执行问题。给定一个工厂,攻击者在一个协调的分布式架构框架中作为一个小组工作,并且有能力编辑一些传感器读数来隐藏故障以混淆操作员。此外,攻击者必须保持隐蔽,也就是说,他们的存在不应该被操作人员发现。为了描述所有可能的潜行攻击集合,建立了一个联合潜行诊断器。我们证明了在上述攻击下的LPN是可诊断的,当且仅当其联合隐式诊断器不存在由故障状态和正常状态或故障状态和不确定状态对组成的循环。提出了一种新的标记功能,以强制植物对尽可能多的攻击进行诊断。给出了实例来说明所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Systems Man Cybernetics-Systems
IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS
CiteScore
18.50
自引率
11.50%
发文量
812
审稿时长
6 months
期刊介绍: The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.
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