Bayesian Network Models in Cyber Security: A Systematic Review

Saba Chockalingam, Wolter Pieters, André Herdeiro Teixeira, Pieter van Gelder

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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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
Number of pages18
ISBN (Electronic)978-3-319-70290-2
ISBN (Print)978-3-319-70289-6
Publication statusPublished - 2017
EventThe 22nd Nordic Conference on Secure IT Systems - Dorpat Convention Centre, Tartu, Estonia
Duration: 8 Nov 201710 Nov 2017

Publication series

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


ConferenceThe 22nd Nordic Conference on Secure IT Systems
Abbreviated titleNordSec 2017
Internet address


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


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