A lightweight intrusion detection method for intelligent substations

Zidong Zhang; Dongqi Liu; Haolan Liang

doi:10.1117/12.3032989

5 July 2024 A lightweight intrusion detection method for intelligent substations

Zidong Zhang, Dongqi Liu, Haolan Liang

Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 1318467 (2024) https://doi.org/10.1117/12.3032989
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

Aiming at the current problem of lack of effective data and high service latency for intrusion detection in smart substations, this paper proposes a lightweight intrusion detection method for smart substations. Through the federated learning method and knowledge distillation method this paper trains a lightweight intrusion detection model based on LSTM. Experiments show that this paper's method has a large improvement in the accuracy and service delay on the NSL-KDD dataset.

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

Citation Download Citation

Zidong Zhang, Dongqi Liu, and Haolan Liang "A lightweight intrusion detection method for intelligent substations", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 1318467 (5 July 2024); https://doi.org/10.1117/12.3032989

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