Guru: Universal Reputation Module for Distributed Consensus Protocols

Biryukov, Alex; Feher, Daniel; Khovratovich, Dmitry

Reference : Guru: Universal Reputation Module for Distributed Consensus Protocols


	Document type :	Reports : Internal report
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/31586

Title :	Guru: Universal Reputation Module for Distributed Consensus Protocols
Language :	English
Author, co-author :	Biryukov, Alex [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) > ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)]
	Feher, Daniel [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Khovratovich, Dmitry [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC) >]
Publication date :	30-Jun-2017
Publisher :	University of Luxembourg
Number of pages :	16
City :	Luxembourg
Country :	Luxembourg
Keywords :	[en] consensus ; distributed ; cryptocurrency ; blockchain
Abstract :	[en] In this paper we describe how to couple reputation systems with distributed consensus protocols to provide high-throughput highly-scalable consensus for large peer-to-peer networks of untrusted validators. We introduce reputation module Guru, which can be laid on top of various consensus protocols such as PBFT or HoneyBadger. It ranks nodes based on the outcomes of consensus rounds run by a small committee, and adaptively selects the committee based on the current reputation. The protocol can also take external reputation ranking as input. Guru can tolerate larger threshold of malicious nodes (up to slightly above 1/2) compared to the 1/3 limit of BFT consensus algorithms.
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/31586

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Open access	Reputation-BFT2017.pdf		Author preprint	279.67 kB	View/Open

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