Sky: Opinion Dynamics Based Consensus for P2P Network with Trust Relationships

TL;DR

This paper introduces a novel opinion dynamics-based consensus method for P2P networks that is resistant to Sybil attacks and adversarial nodes, leveraging trust relationships and local interactions without requiring global network information.

Contribution

It proposes the first opinion dynamics model tailored for P2P consensus, demonstrating improved convergence and fault tolerance over existing models.

Findings

The Sky model converges faster than MR, voter, and Sznajd models.

The approach tolerates at least 13% random node failures and 2% influential node failures.

Over 96% correct nodes reach consensus within 70 seconds on a large network.

Abstract

Traditional Byzantine consensus does not work in P2P network due to Sybil attack while the most prevalent Sybil-proof consensus at present still can't resist adversary with dominant compute power. This paper proposed opinion dynamics based consensus for P2P network with trust relationships, consisting of the sky framework and the sky model. With the sky framework, opinion dynamics can be applied in P2P network for consensus which is Sybil-proof through trust relationships and emerges from local interactions of each node with its direct contacts without topology, global information or even sample of the network involved. The sky model has better performance of convergence than existing models including MR, voter and Sznajd, and its lower bound of fault tolerance performance is also analyzed and proved. Simulations show that our approach can tolerant failures by at least 13% random nodes or 2% top influential nodes while over 96% correct nodes still make correct decision within 70 seconds on the SNAP Wikipedia who-votes-on-whom network for initial configuration of convergence>0.5 with reasonable latencies. Comparing to compute power based consensus, our approach can resist any faulty or malicious nodes by unfollowing them. To the best of our knowledge, it's the first work to bring opinion dynamics to P2P network for consensus.