Towards feature engineering for intrusion detection in IEC-61850 communication networks

Quincozes, Vagner; Ereno Quincozes, Silvio; Passos, Diego; Albuquerque, Célio; Mosse, Daniel

http://hdl.handle.net/10400.21/22135

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Authors

Quincozes, Vagner

Ereno Quincozes, Silvio

Passos, Diego

Albuquerque, Célio

Mosse, Daniel

Abstract(s)

Digital electrical substations are fundamental in providing a reliable basis for smart grids. However, the deployment of the IEC-61850 standards for communication between intelligent electronic devices (IEDs) brings new security challenges. Intrusion detection systems (IDSs) play a vital role in ensuring the proper function of digital substations services. However, the current literature lacks efficient IDS solutions for certain classes of attacks, such as the masquerade attack. In this work, we propose the extraction and correlation of relevant multi-layer information through a feature engineering process to enable the deployment of machine learning-based IDSs in digital substations. Our results demonstrate that the proposed solution can detect attacks that are considered challenging in the literature, attaining an F1-score of up to 95.6% in the evaluated scenarios.

Keywords

Feature extraction Intrusion detection systems (IDSs) Intrusion detection systems IDSs Machine learning ML Digital substations IEC-61850

URI

http://hdl.handle.net/10400.21/22135

Citation

Quincozes, V. E., Quincozes, S. E., Passos, D., Albuquerque, C., & Mosse, D. (2024). Towards feature engineering for intrusion detection in IEC-61850 communication networks. Annals of Telecommunications. 79(7-8), SI, 537-551. https://doi.org/10.1007/s12243-024-01011-x