Reinforcement Learning-Based Approaches for Enhancing Security and Resilience in Smart Control: A Survey on Attack and Defense Methods

arXiv:2402.15617v1 Announce Type: new
Abstract: Reinforcement Learning (RL), one of the core paradigms in machine learning, learns to make decisions based on real-world experiences. This approach has significantly advanced AI applications across various domains, notably in smart grid optimization and smart home automation. However, the proliferation of RL in these critical sectors has also exposed them to sophisticated adversarial attacks that target the underlying neural network policies, compromising system integrity. Given the pivotal role of RL in enhancing the efficiency …

advanced applications arxiv attack control cs.cr cs.sy defense domains eess.sy experiences grid home machine machine learning optimization real resilience security smart smart grid smart home survey world