Ensemble Learning Methods for Anomaly Intrusion Detection System in Smart Grid

• Published in: IEEE International Conference on Electro Information Technology pp. 129 - 135
• Main Authors: Khoei, Tala Talaei, Aissou, Ghilas, Hu, When Chen, Kaabouch, Naima
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.05.2021
• Subjects: anomaly-based; bagging; Benchmark testing; boosting; DDoS attacks; ensemble learning; Feature extraction; Intrusion detection; intrusion detection system; Learning systems; Performance evaluation; performance metrics; Reflection; Simulation; Smart grid; stacking; supervised machine learning

Smart grid is an emerging technology that delivers intelligently to the end-users through two-way communication. However, this technology can be subject to several cyber-attacks due to this network's inherent weaknesses. One practical solution to secure smart grid networks is using an intrusion...