Adaptive Learning for IRS-Assisted Wireless Networks: Securing Opportunistic Communications Against Byzantine Eavesdroppers

This paper introduces a unified learning framework for Byzantine-resilient spectrum sensing and secure transmission in intelligent reflecting surface (IRS)-assisted networks under channel state information (CSI) uncertainty. The sensing module employs robust Bayesian belief updates with adversary-resistant aggregation and consensus, guaranteeing reliable primary user (PU) detection even when a bounded fraction of users are malicious. Based on the sensing outcome, the transmission module formulat