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

  • Houwu Chen
  • Jiwu Shu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9530)

Abstract

Traditional Byzantine consensus does not work in P2P network due to Sybil attack while the most prevalent Sybil-proof consensus at present can’t resist adversary with dominant compute power. This paper proposed opinion dynamics based consensus consisting of a framework and a model. With the framework, opinion dynamics can be applied in P2P network for consensus which is Sybil-proof and emerges from local interactions of each node with its direct contacts without topology, global information or even sample of the network involved. The model has better performance of convergence than existing opinion dynamics models, and its lower bound of fault tolerance performance is also analyzed and proved. Simulations show that our approach can tolerate failures by at least \(13\,\%\) random nodes or \(2\,\%\) top influential nodes while over \(96\,\%\) correct nodes still make correct decision within 70 s 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.

Keywords

Opinion dynamics P2P Byzantine consensus Sybil attack 

Notes

Acknowledgments

The authors would like to greatly appreciate the anonymous reviewers for their insightful comments. This work was supported by the National Natural Science Foundation of China (Grant No. 61433008), the National High Technology Research and Development Program of China (Grant No. 2013AA013201), and Project of science and technology of Beijing City (Grant No. D151100000815003).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computer Science and TechnologyTsinghua UniversityBeijingChina

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