文章基本信息

标题：Malicious Anomaly Detection Approaches Robustness in Manufacturing ICSs
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作者：Amaury Beaudet ; Cédric Escudero ; Éric Zamaï 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：1
页码：146-151
DOI：10.1016/j.ifacol.2021.08.016
语种：English
出版社：Elsevier
摘要：AbstractFor the past decade, manufacturing Industrial Control Systems (ICSs) have suffered from targeted attacks against their physical system and their control integrity, resulting in financial and material losses. Among protective answers to this malicious threat, Anomaly Detection Systems (ADS) based on behavioral models of the ICS are highly regarded for their ability to detect zero-day attacks. However, the design of accurate and non-obsolescent detection models is not as an easy task in a constantly changing ICS environment. Thus, this paper provides an overview of the behavioral ADSs detection flaws issued from the ICS unpredictable management and its heterogeneous environment. Behavioral models will be introduced in light of four attributes: their design method, the modeled ICS behavior, the lifecycle of the design and the model nature. Then, each of these attributes will be discussed in regard of their detection robustness to the different environmental factors and uncertainties they are affected by.
关键词：KeywordsCyber-securityICSAnomaly Detection SystemsManufacturing Systems