2021/02/12 by Apostolos I. Rikos, Themistoklis Charalambous, Rikos, Apostolos I. +6 · 1 citation
Computer Science · Engineering · Mathematics · #Cryptography and Data Security #Distributed systems and fault tolerance #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Privacy-Preserving Technologies in Data #Systems and Control (eess.SY) #cs.SY #eess.SY #electronic engineering #information engineering #math.OC
paper · pdf · doi:10.48550/arxiv.2102.06778
12 pages
arxiv created 2021/02/12 · openalex publication_date 2021/02/12 · arxiv updated 2021/02/16 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
In this paper, we consider the problem of privacy preservation in the average consensus problem when communication among nodes is quantized. More specifically, we consider a setting where some nodes in the network are curious but not malicious and they try to identify the initial states of other nodes based on the data they receive during their operation (without interfering in the computation in any other way), while some nodes in the network want to ensure that their initial states cannot be inferred exactly by the curious nodes. We propose two privacy-preserving event-triggered quantized average consensus algorithms that can be followed by any node wishing to maintain its privacy and not reveal the initial state it contributes to the average computation. Every node in the network (including the curious nodes) is allowed to execute a privacy-preserving algorithm or its underlying average consensus algorithm. Under certain topological conditions, both algorithms allow the nodes who adopt privacypreserving protocols to preserve the privacy of their initial quantized states and at the same time to obtain, after a finite number of steps, the exact average of the initial states.