Power distribution networks play a crucial role in modern society by delivering electricity from transmission grids to end-users, making their security and reliability paramount. With the increasing prevalence of cyber threats targeting these networks, traditional protection methods are no longer sufficient, necessitating the integration of advanced technologies to enhance security. This paper explores artificial intelligence (AI)-empowered communication techniques, including 5G virtual local area networks (LANs), network digital twins, and radio frequency fingerprinting, to address the growing cybersecurity challenges in power distribution networks. These techniques leverage AI techniques to provide robust solutions for network protection, ensuring the safe and efficient transmission of electrical energy. However, challenges such as the lack of high-quality multi-modal data, insufficient data analysis capacity, and limited local computing resources remain. The paper proposes potential solutions, including multi-modal learning, industrial large language models (LLMs), and cloud-edge collaboration, to overcome these challenges and enhance the security and efficiency of power distribution networks. The findings highlight the significance of integrating AI and advanced communication technologies to safeguard critical infrastructure against emerging cyber threats, emphasizing the need for further research and collaboration to fully realize the potential of these solutions.
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Bai et al. (2025) studied this question.
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