Research on abnormal traffic detection in power grid network based on Naive Bayesian Gaussian model

Jie Wang; Zhiming Zhong

doi:10.1117/12.3038162

7 August 2024 Research on abnormal traffic detection in power grid network based on Naive Bayesian Gaussian model

Jie Wang, Zhiming Zhong

Proceedings Volume 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024); 132291J (2024) https://doi.org/10.1117/12.3038162
Event: Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 2024, Nanchang, China

Abstract

The power grid control system is facing the threat of cyber attacks. Based on the Naive Bayes algorithm is an effective way to detect the abnormal traffic of the grid network. First, design the abnormal detection framework based on the semantic characteristics of Naive Bayes. Then, the data pre-processing of the data in the industrial control system was conducted, and the feature vector was constructed according to the functions, instructions, points and other fields in the network data of the industrial control system. However, designing a Naive Bayes Gaussian abnormal detection model, the state of normal/abnormal systems in the network data stream, control behavior recognition and detection. Finally, this method detects the abnormal MMS protocol of the power grid system to verify the detection effectiveness of the method.

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

Citation Download Citation

Jie Wang and Zhiming Zhong "Research on abnormal traffic detection in power grid network based on Naive Bayesian Gaussian model", Proc. SPIE 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 132291J (7 August 2024); https://doi.org/10.1117/12.3038162

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