Artificial Intelligence Enabled Network Intrusion Detection Model (AI-NIDM) for Smart Grid Cyber-Physical Systems - Dhanasekaran, P.; V., Sakthivel; Jayashri, N.; Hemawathi, M. S.; Kaliappan, Vishnu Kumar (International Journal of Intelligent Systems and Applications in Engineering, 2023)
The increasing complexity and interconnectivity of Smart Grid Cyber-Physical Systems (SG-CPS) have raised significant concerns regarding the security and integrity of these systems. Network Intrusion Detection Model (NIDM) is an essential component of SG-CPS security infrastructure. However, the conventional rule-based and signature-based NIDM are becoming less effective in detecting advanced and sophisticated cyber-attacks. Artificial Intelligence (AI) technologies, named machine learning, deep learning, and neural networks, have shown great potential in enhancing the accuracy and efficiency of NIDM. This paper proposes an AI-Enabled Network Intrusion Detection Model (AI-NIDM) called GWA-ANN for SG-CPS, which integrates AI techniques with traditional NIDS for improved detection and response to cyber-attacks. The proposed system is evaluated on a public SG-CPS dataset, and the results establish that AI-NIDM can effectively detect and classify various types of cyber-attacks with high accuracy and low false-positive rates. The proposed AI-NIDM can significantly improve the security and resilience of SG-CPS against emerging cyber threats.