Assessing Information Security Risk Using Markov Chain

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

  • Daniel Tse
  • Xiaoting Pan
  • Yuan Zong
  • Jiaxi Liu
  • Qinyan Yang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publication2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018
PublisherIEEE
Pages808-813
ISBN (Electronic)978-1-5386-6786-6
Publication statusPublished - Dec 2018

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
Volume2019-December
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Title2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018
PlaceThailand
CityBangkok
Period16 - 19 December 2018

Abstract

[1] Information leakage occurs several times in universities in recent years. In this article, we propose a risk assessment method based on Markov chain for universities to evaluate risks using menace index. After identifying the assets and threats in universities, we use a survey data of university risks to find out the probability of the occurrence of each threat. Markov chain is used to indicate the probability of future. The result of a predicted severity sequence of risks can be useful to universities which risks they should pay more attention to. Two methods are used in the Markov part: One is the traditional way to set the initial probability matrix; the other is a statistical probability to present each menace in the initial probability matrix. After comparison, we found that the second method is more precise for risk assessment.

Research Area(s)

  • Markov Chain, Menace Index, Security Risk Assessment

Citation Format(s)

Assessing Information Security Risk Using Markov Chain. / Tse, Daniel; Pan, Xiaoting; Zong, Yuan et al.

2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018. IEEE, 2018. p. 808-813 8607422 (IEEE International Conference on Industrial Engineering and Engineering Management; Vol. 2019-December).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review