Current perspectives on smart grid cybersecurity and critical infrastructure protection

  • Puneet Garg Department of CSE-AI, KIET Group of Institutions, Delhi NCR, Ghaziabad, India
DOI https://doi.org/10.55670/fpll.fuen.5.4.3
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Abstract

The increasing convergence of renewable energy sources, information and communication technology, Internet of Things devices, smart meters, and phasor measurement units has enhanced the efficiency, reliability, and real-time operation of Smart Grids. However, this interconnected cyber-physical infrastructure has also increased cybersecurity vulnerabilities and attack surfaces. This paper reviews AI/ML-based security approaches for Smart Grid cybersecurity and critical infrastructure protection, focusing on major threats such as False Data Injection Attacks, Denial-of-Service attacks, Man-in-the-Middle attacks, spoofing, malware, and malicious command injection. The study examines existing protection mechanisms, including authentication and access control, intrusion detection, attack mitigation, secure communication, data protection, and privacy preservation. The study further discusses cyber-physical system protection, resilience, incident response, continuous monitoring, network segmentation, and AI/ML-based security approaches. A review of recent research highlights advances in anomaly detection, trust management, multilayer security, and intelligent threat detection. However, challenges remain in scalability, real-time processing, interoperability, adaptive defense, limited datasets, and real-world validation. The findings emphasize the need for integrated, intelligent, scalable, and adaptive cybersecurity approaches to strengthen Smart Grid resilience, reliability, availability, and operational continuity.

Graphical Abstract
Keywords
Smart Grid cybersecurity Cyber-attacks Critical infrastructure protection Intrusion detection Cyber resilience
How to Cite
Garg, Puneet. 2026. “Current Perspectives on Smart Grid Cybersecurity and Critical Infrastructure Protection”. Future Energy 5 (4):18-25. https://doi.org/10.55670/fpll.fuen.5.4.3.
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