Authored by:
Christian Cachin, University of Bern
Daniel Collins, University of Sydney
Tyler Crain, University of Sydney
Vincent Gramoli, University of Sydney
Collecting anonymous opinions has applications from whistleblowing to complex voting, where participants rank candidates by order of preference. Unfortunately, as far as we know, there is no efficient distributed solution to this problem. Previous solutions either require trusted third parties, are inefficient or sacrifice anonymity.
In this paper, we propose a distributed solution called the Anonymised Vector Consensus Protocol (AVCP) that reduces the problem of agreeing on a set of anonymous votes to the binary Byzantine consensus problem. The key idea to preserve the anonymity of voters—despite some of them act-ing maliciously—is to detect double votes through traceable ring signatures. AVCP is resilient-optimal as it tolerates up to a third of Byzantine participants.
We prove our algorithm correct and show that it preserves anonymity with, at most, linear communication overhead and constant message overhead when compared to a recent consensus baseline.
Finally, we demonstrate empirically that the protocol is practical by deploying it on 100 machines geo-distributed in three continents: America, Asia and Europe. Anonymous decisions are reached within 10 seconds with a conservative choice of traceable ring signatures.
Download Paper
This paper was co-authored by our CTO and Founder Professor Vincent Gramoli.
Professor Vincent Gramoli is a full professor at the University of Sydney. He is a researcher in the field of distributed systems and algorithms, with a focus on the design and analysis of distributed systems and algorithms for shared memory and data-centric systems, including distributed hash tables, distributed shared memory and transactional memory. He has published numerous papers in top-tier conferences and journals in the field and has received several awards for his research. He is also currently serving as the Head of Concurrent Systems Research Group at the University of Sydney.