An Attention-Based Deep Generative Model for Anomaly Detection in Industrial Control Systems

arXiv:2405.05277v1 Announce Type: new
Abstract: Anomaly detection is critical for the secure and reliable operation of industrial control systems. As our reliance on such complex cyber-physical systems grows, it becomes paramount to have automated methods for detecting anomalies, preventing attacks, and responding intelligently. {This paper presents a novel deep generative model to meet this need. The proposed model follows a variational autoencoder architecture with a convolutional encoder and decoder to extract features from both spatial and temporal dimensions. Additionally, we …

abstract anomaly anomaly detection arxiv attacks attention automated control control systems cs.lg cyber detection generative industrial industrial control novel paper reliance systems type