Tracking Under Fire: Resilient Distributed Average Tracking Under Dual‐Channel DoS Attack

ABSTRACT Distributed Average Tracking (DAT) enables a network of agents to cooperatively track the average of their time‐varying reference signals without centralized coordination. Nearly all existing DAT designs assume ideal communication conditions, an assumption that is often unrealistic in practical networked systems. In this work, we study DAT in the presence of Denial‐of‐Service (DoS) attacks that can block both inter‐agent communication links and reference‐to‐agent connections. We model these dual‐channel DoS scenarios and develop a simple yet effective distributed estimator that adapts to changing network topology while maintaining average tracking. Rigorous mathematical analyses are provided to quantify the effect of attacks in both channels on estimator performance. Simulation studies illustrate how the proposed approach limits tracking degradation under different DoS patterns. The results provide insights for designing resilient DAT algorithms in safety‐critical and adversarial environments.