Research on new power business threat modeling method based on Bayesian networks

Yong Li; Tao Zhang; Zhipeng Shao; Mu Chen; Yuanyuan Ma

doi:10.1117/12.3033224

5 July 2024 Research on new power business threat modeling method based on Bayesian networks

Yong Li, Tao Zhang, Zhipeng Shao, Mu Chen, Yuanyuan Ma

Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131840N (2024) https://doi.org/10.1117/12.3033224
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

The emerging power system, predominantly reliant on renewable energy sources, drives the future diversification of enduse energy structures. However, within this new power system, business terminals encounter various access risks. Terminals within unmanned aerial vehicle (UAV) power inspection systems, distributed photovoltaic business, and vehicular networking are susceptible to network attacks, exposing them to risks of information leakage. To address the security threats prevalent in the emerging power industry, this paper proposes a Bayesian network-based threat modeling approach. Building upon this, a probabilistic graphical model-based threat risk assessment scheme is presented. Furthermore, typical interaction scenarios of novel power system operations are selected to demonstrate the effectiveness of the model by employing Bayesian networks for modeling and simulation validation.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yong Li, Tao Zhang, Zhipeng Shao, Mu Chen, and Yuanyuan Ma "Research on new power business threat modeling method based on Bayesian networks", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131840N (5 July 2024); https://doi.org/10.1117/12.3033224

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