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Key path analysis method for large-scale industrial control network

  • Yaofang Zhang
  • , Zheyu Zhang
  • , Haikuo Qu
  • , Ge Zhang
  • , Zibo Wang
  • , Bailing Wang*
  • *Corresponding author for this work
  • School of Computer Science and Technology (School of Software), Harbin Institute of Technology Weihai
  • China Industrial Control Systems Cyber Emergency Response Team
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

In order to solve the problem of high time-consuming and resource-consuming quantitative calculation of large-scale industrial control network attack graphs, a key path analysis method for large-scale industrial control networks was proposed. Firstly, the idea of cut set was used to calculate the key nodes set of Bayesian attack graph by combining the atomic attack income in industrial control network, which solved the problem that the current cut set algorithm only considers the key nodes in graph structure. Secondly, a dynamic updating strategy of Bayesian attack graph which only updated the attack probability of key nodes was proposed to efficiently calculate the attack probability of the whole graph and analyze the key path of attack graph. The experimental results show that the proposed method can not only ensure the reliability of the calculation results of large-scale industrial control attack graphs, but also can significantly reduce the time consumption and have a significant improvement in the calculation efficiency.

Original languageEnglish
Pages (from-to)31-43
Number of pages13
JournalChinese Journal of Network and Information Security
Volume7
Issue number6
DOIs
StatePublished - 15 Dec 2021
Externally publishedYes

Keywords

  • Attack graph
  • Bayesian network
  • Industrial control network
  • Key node
  • Key path

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