Privacy-Preserving Average Consensus for Swarm Systems Subject to DoS Attacks

warm systems have attracted growing interest due to Internet of Things (IoT) advancements and their applications in multi-robot control, environmental mapping, and intelligent transportation. Average consensus protocols are crucial in these scenarios, but current implementations require frequent interagent data exchange, posing significant risks to network security. warm systems have attracted growing interest due to Internet of Things (IoT) advancements and their applications in multi-robot control, environmental mapping, and intelligent transportation. Average consensus protocols are crucial in these scenarios, but current implementations require frequent interagent data exchange, posing significant risks to network security. In this paper, we present a privacy-preserving consensus algorithm designed to ensure the privacy of the initial state while achieving consensus on the precise average of the initial values, even in the presence of denial-of-service (DoS) attacks. First, to protect agent state privacy, we introduce perturbation to the transmitted information among the agents using independently generated random noises drawn from Laplace distributions, in conjunction with the utilization of specifically designed pseudo-random values. Then, by synthesizing the perturbed average consensus algorithm with an event-triggered control strategy, a distributed privacy-preserving consensus protocol is established for the swarm systems under DoS attacks. The presented results indicate that under the given network communication conditions, the event-triggered mechanism can effectively withstand the impact of DoS attacks on the network and ensure the achievement of accurate average consensus. Finally, experimental results on a UAV-swarm board based Wi-Fi network are provided to validate the effectiveness of obtained theoretical results.