M. Aljabri

Adversarial Machine Learning in Industrial IoT: A Systematic Review of Attack Realism, Defense Trade-Offs, and Deployment Gaps

This SLR analyzes 50 research articles to provide a holistic view of AML threats in IIoT systems and identifies seven distinct attack types: gradient-based perturbations, GAN-generated samples, poisoning attacks, reinforcement learning-based (RL) strategies, saliency-based feature manipulation, false data injection, and hybrid approaches.