Bayesian Network Models in Cyber Security: A Systematic Review

Conference Paper (2017)
Author(s)

Sabarathinam Chockalingam (TU Delft - Safety and Security Science)

W Pieters (TU Delft - Safety and Security Science)

André Herdeiro Teixeira (TU Delft - Information and Communication Technology)

Pieter Van Gelder (TU Delft - Safety and Security Science)

Safety and Security Science
Copyright
© 2017 S. Chockalingam, W. Pieters, A.M. Herdeiro Teixeira, P.H.A.J.M. van Gelder
DOI related publication
https://doi.org/10.1007/978-3-319-70290-2_7
More Info
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Publication Year
2017
Language
English
Copyright
© 2017 S. Chockalingam, W. Pieters, A.M. Herdeiro Teixeira, P.H.A.J.M. van Gelder
Safety and Security Science
Volume number
10674
Pages (from-to)
105-122
ISBN (print)
978-3-319-70289-6
ISBN (electronic)
978-3-319-70290-2
Reuse Rights

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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.

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