SA-IDS: a self-supervised and adaptive intrusion detection system for edge-based IIoT security with label-free drift resilience
SA-IDS is proposed, a self-supervised and adaptive intrusion detection framework designed for resource-constrained IIoT edge devices that leverages contrastive self-supervised learning to learn robust representations of benign telemetry data without requiring labeled attacks.