Paper
5 June 2024 Intelligent monitoring of malicious intrusion behavior for power communication network channel
Hongyu Shi, Haiying Huang, Yong Wu, Mengtong Li, Qiankun Zhang
Author Affiliations +
Proceedings Volume 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024); 1316365 (2024) https://doi.org/10.1117/12.3030454
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 2024, Xi'an, China
Abstract
When monitoring network malicious intrusion, the reliability of monitoring results is low due to the gradual development of network intrusion. Therefore, an intelligent monitoring method for malicious intrusion in power communication network channel is proposed. Combined with the actual situation of different power communication network environments, the channel parameters of the more sensitive power communication network are taken as the main acquisition target. After normalization, the overall operation status of each node in the power communication network channel is determined. In the malicious intrusion behavior monitoring phase, the control ability of the node itself and the health degree of the node in the power communication network channel are taken as the core, and the survival degree of the node is calculated to achieve accurate monitoring of malicious intrusion behavior. In the test results, the effective monitoring rate of the design method for different types of malicious intrusion behaviors is stable in the range of 91.0% - 93.0%, and the false alarm rate is basically stable in the range of 4.0% - 6.5%, with high reliability.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Hongyu Shi, Haiying Huang, Yong Wu, Mengtong Li, and Qiankun Zhang "Intelligent monitoring of malicious intrusion behavior for power communication network channel", Proc. SPIE 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 1316365 (5 June 2024); https://doi.org/10.1117/12.3030454
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KEYWORDS
Network security

Deep learning

Design

Data processing

Environmental sensing

Analytical research

Data communications

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