XAI-Guided Physical Adversarial Machine Learning Attacks on Automatic Modulation Classification

With the advancement of Artificial Intelligence (AI) and Explainable AI (XAI), Deep Learning (DL) algorithms become increasingly vulnerable to adversarial machine learning (AML) threats. One of the widely used DL-based applications in wireless communication is the Automatic Modulation Classification (AMC). In this paper, we investigate XAI methods for designing AML attacks in DL-based AMC systems. Specifically, we discuss four AML tactics, namely, untargeted causative, targeted evasion, untarget