Bayesian Network Models in Cyber Security: A Systematic Review

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Abstract

Bayesian Networks (BNs) are an increasingly popular modelling technique in cyber security especially due to their capability to overcome data limitations. This is also instantiated by the growth of BN models development in cyber security. However, a comprehensive comparison and analysis of these models is missing. In this paper, we conduct a systematic review of the scientific literature and identify 17 standard BN models in cyber security. We analyse these models based on 9 different criteria and identify important patterns in the use of these models. A key outcome is that standard BNs are noticeably used for problems especially associated with malicious insiders. This study points out the core range of problems that were tackled using standard BN models in cyber security, and illuminates key research gaps.
Original languageEnglish
Title of host publicationProceedings of the Nordic Conference on Secure IT Systems (Nordic 2017)
EditorsHelger Lipmaa, Aikaterini Mitrokotsa, Raimundas Matulevicius
PublisherSpringer
Pages105-122
Number of pages18
Volume10674
ISBN (Electronic)978-3-319-70290-2
ISBN (Print)978-3-319-70289-6
DOIs
Publication statusE-pub ahead of print - 4 Nov 2017
EventThe 22nd Nordic Conference on Secure IT Systems - Dorpat Convention Centre, Tartu, Estonia
Duration: 8 Nov 201710 Nov 2017
http://nordsec2017.cs.ut.ee/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10674
ISSN (Print)0302-9743

Conference

ConferenceThe 22nd Nordic Conference on Secure IT Systems
Abbreviated titleNordSec 2017
CountryEstonia
CityTartu
Period8/11/1710/11/17
Internet address

Keywords

  • Bayesian attack graph
  • Bayesian Network
  • Cyber security
  • Information security
  • Insider threat

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  • Cite this

    Chockalingam, S., Pieters, W., Herdeiro Teixeira, A., & van Gelder, P. (2017). Bayesian Network Models in Cyber Security: A Systematic Review. In H. Lipmaa, A. Mitrokotsa, & R. Matulevicius (Eds.), Proceedings of the Nordic Conference on Secure IT Systems (Nordic 2017) (Vol. 10674, pp. 105-122). (Lecture Notes in Computer Science; Vol. 10674). Springer. https://doi.org/10.1007/978-3-319-70290-2_7