Covert Communication Under Stochastic Resonance Eavesdropping: Analysis and Design

This paper investigates covert communication in the presence of an eavesdropper employing stochastic resonance (SR)–based detection. A unified analytical model is developed to characterize nonlinear noise-matching detectors, with SR serving as a representative example. Closed-form expressions for the achievable covert rate are derived under a KL-divergence-based covertness constraint, revealing that SR-enabled eavesdroppers can significantly enhance detection performance under perfectly matched noise conditions. More importantly, this work establishes a fundamental performance–robustness tradeoff: although stochastic resonance can amplify weak signals, its detection gain is highly sensitive to noise-level mismatch and interference uncertainty. We prove that under random or unknown interference, the worst-case detection performance of SR-based detectors is strictly inferior to that of conventional linear detectors, such as energy detection. This result demonstrates that the detection advantage offered by stochastic resonance is not free and inevitably comes at the cost of robustness. Numerical results validate the theoretical analysis and show that random, fast-varying interference constitutes a minimax-optimal strategy for covert transmission when the eavesdropper's detection model is unknown. These findings provide new insights into the fundamental limits of covert communication against advanced nonlinear detectors.