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文章基本信息

  • 标题:Statistical Approach to Detection of Attacks for Stochastic Cyber-Physical Systems
  • 本地全文:下载
  • 作者:Damián Marelli ; Tianju Sui ; Minyue Fu
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:25
  • 页码:178-183
  • DOI:10.1016/j.ifacol.2018.11.101
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractWe study the problem of detecting an attack on a stochastic cyber-physical system. We start by proposing a detection criterion based on checking the statistics of the Kalman prediction error. To show the importance of the proposed criterion, we study certain attacking schemes which can be effectively detected by this criterion, but not by checking simpler conditions based on commonly used statistics. We then use the proposed criterion to derive a detection algorithm. This algorithm is based on a statistical confidence test, giving a confidence level for detecting an attack. We present simulation results to illustrate the performance of this algorithm.
  • 关键词:KeywordsSystem securitylinear systemscyber-physical systemsintegrity attacksattack detectionstatistical hypothesis testing
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