文章基本信息

标题：Optimal Stealthy Attack under KL Divergence and Countermeasure with Randomized Threshold
本地全文：下载
作者：Enoch Kung ; Subhrakanti Dey ; Ling Shi 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：9496-9501
DOI：10.1016/j.ifacol.2017.08.1587
语种：English
出版社：Elsevier
摘要：AbstractIn a cyber-physical system, there are potential sources of malicious attacks that can damage the estimation quality in an underlying network control system. The attacker aims to maximize these damages while the estimator attempts to minimize them. In this paper we define an attack’s stealth based on the KL divergence and obtain an optimal attack. Furthermore, we suggest one method in which the estimator may limit the damage to the system while imposing on any attack a probability for it to be non-stealthy.
关键词：KeywordsCyber-Physical SystemsDetectionSecurity