Author

Maziar Asmani

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Sep 2026

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.

Mahdi Ajdani, Maziar Asmani · Cluster Computing · 0 citations