Bayesian Network Models in Cyber Security: A Systematic Review

Conference paper (2017)

Authors

S. Chockalingam Safety and Security Science - TPM
W. Pieters Safety and Security Science - TPM
P.H.A.J.M. van Gelder Safety and Security Science - TPM
Research Group
Safety and Security Science (TPM) (TU Delft)
Copyright: © 2017 S. Chockalingam, W. Pieters, A.M. Herdeiro Teixeira, P.H.A.J.M. van Gelder
DOI: https://doi.org/10.1007/978-3-319-70290-2_7
Cyber security Bayesian Network Information security Insider threat Bayesian attack graph
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Published Date

2017

Language

English

Reuse Rights

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Faculty

Technology, Policy and Management

Department

Values Technology and Innovation

Research Group

Safety and Security Science

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.