Exploring the emerging role of large language models in smart grid cybersecurity: a survey of attacks, detection mechanisms, and mitigation strategies

Abstract

Smart grids are modernizing the future of providing energy for everyone, allowing us to increase the efficiency of power generation, transmission, or distribution using information and communication technologies. However, the network structure of smart grids makes them vulnerable to varying levels of cyber threats. This paper provides a broad overview of cyber threats against smart grids, considering attack surfaces, communication network layers, and the core security triad of confidentiality, integrity, and availability. This survey also outlines emerging threats and covers current protection, prevention, detection, mitigation, and recovery measures, focusing on emerging technologies such as artificial intelligence and large language models (LLMs) in smart grid security. We analyze and show how previous work has tackled and approached similar themes in this area. Amongst our contributions are categorizing the critical parts of smart grids that are most vulnerable to attack, several threat taxonomies, and a review of the increasing importance of LLMs for enhancing grid security. This evaluation underscores the need for effective and robust security technologies to avoid the compromises that result from more sophisticated cyber attacks.