Privacy-Preserving Average Consensus via Pulse-Coupled Oscillators

Average consensus is a cornerstone of distributed systems, facilitating essential functionalities such as distributed information fusion, decision-making, and decentralized control. Achieving average consensus typically relies on explicit exchanges of state and identity information among neighboring nodes. This reliance poses a risk of exposing sensitive information, leading to unpredictable data leakage. Therefore, it is imperative to implement privacy-preserving mechanisms within average consensus protocols. However, existing privacy-preserving approaches primarily focus on protecting the initial states of all nodes, compromising the identity information of the nodes. This vulnerability can be particularly problematic in scenarios where preserving identity information is paramount. In this paper, we propose a novel pulse-coupled oscillator-based privacy-preserving average consensus algorithm. Unlike traditional methods that exchange explicit state information through data packet transmission, our approach utilizes simple, identical, and content-free pulses. This method not only enhances the preservation of identity information but is also well-suited for hostile communication environments, such as during jamming attacks that disrupt data packet transmission. Furthermore, our algorithm does not necessitate synchronized clocks among all nodes, enhancing its suitability for practical applications. Numerical simulations are presented to validate the effectiveness of our theoretical results.