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Dynamic Security Risk Evaluation via Hybrid Bayesian Risk Graph in Cyber-Physical Social Systems

Li, Shancang; Zhao, Shanshan; Yuan, Yong; Sun, Qindong; Zhang, Kewang

Authors

Shancang Li Shancang.Li@uwe.ac.uk
Senior Lecturer in Computer Forensics and Security

Shanshan Zhao shanshan.zhao@uwe.ac.uk

Yong Yuan

Qindong Sun

Kewang Zhang



Abstract

© 2014 IEEE. Cyber-physical social system (CPSS) plays an important role in both the modern lifestyle and business models, which significantly changes the way we interact with the physical world. The increasing influence of cyber systems and social networks is also a high risk for security threats. The objective of this paper is to investigate associated risks in CPSS, and a hybrid Bayesian risk graph (HBRG) model is proposed to analyze the temporal attack activity patterns in dynamic cyber-physical social networks. In the proposed approach, a hidden Markov model is introduced to model the dynamic influence of activities, which then be mapped into a Bayesian risks graph (BRG) model that can evaluate the risk propagation in a layered risk architecture. Our numerical studies demonstrate that the framework can model and evaluate risks of user activity patterns that expose to CPSSs.

Journal Article Type Article
Publication Date Dec 1, 2018
Journal IEEE Transactions on Computational Social Systems
Electronic ISSN 2329-924X
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 5
Issue 4
Pages 1133-1141
APA6 Citation Li, S., Zhao, S., Yuan, Y., Sun, Q., & Zhang, K. (2018). Dynamic Security Risk Evaluation via Hybrid Bayesian Risk Graph in Cyber-Physical Social Systems. IEEE Transactions on Computational Social Systems, 5(4), 1133-1141. https://doi.org/10.1109/TCSS.2018.2858440
DOI https://doi.org/10.1109/TCSS.2018.2858440
Keywords activity profile modelling, risk analysis, Hidden Markov Model, Bayesian risk graph, cyber-physical social system
Publisher URL http://dx.doi.org/10.1109/TCSS.2018.2858440
Additional Information Additional Information : (c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

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