A fine-grained reputation system for reliable service selection in peer-to-peer networks

Yanchao Zhang, Yuguang Fang

Research output: Contribution to journalArticle

77 Citations (Scopus)

Abstract

Distributed peer-to-peer (P2P) applications have been gaining momentum recently. In such applications, all participants are equal peers simultaneously functioning as both clients and servers to each other. A fundamental problem is, therefore, how to select reliable servers from a vast candidate pool. To answer this important open question, we present a novel reputation system built upon the multivariate Bayesian inference theory. Our system offers a theoretically sound basis for clients to predict the reliability of candidate servers based on self-experiences and feedbacks from peers. In our system, a fine-grained quality of service (QoS) differentiation method is designed to satisfy the diverse QoS needs of individual nodes. Our reputation system is also application-independent and can simultaneously serve unlimited P2P applications of different type. Moreover, it is semi-distributed in the sense that all applicationrelated QoS information is stored across system users either in a random fashion or through a distributed hash table (DHT). In addition, we propose to leverage credits and social awareness as reliable means of seeking honest feedbacks. Furthermore, our reputation system well protects the privacy of users offering feedbacks and is secure against various attacks such as defaming, flattering, and the Sybil attack. We confirm the effectiveness and efficiency of the propose system by extensive simulation results.

Original languageEnglish (US)
Pages (from-to)1134-1145
Number of pages12
JournalIEEE Transactions on Parallel and Distributed Systems
Volume18
Issue number8
DOIs
StatePublished - Aug 2007
Externally publishedYes

Fingerprint

Reputation System
Service Selection
Peer to peer networks
Peer-to-peer Networks
Quality of Service
Quality of service
Servers
Server
Feedback
Attack
Service Differentiation
Peer-to-peer (P2P)
Bayesian inference
Leverage
Privacy
Table
Momentum
Acoustic waves
Predict
Vertex of a graph

Keywords

  • DHT
  • P2P
  • QoS
  • Reliability
  • Reputation
  • Security

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Theoretical Computer Science
  • Computational Theory and Mathematics

Cite this

A fine-grained reputation system for reliable service selection in peer-to-peer networks. / Zhang, Yanchao; Fang, Yuguang.

In: IEEE Transactions on Parallel and Distributed Systems, Vol. 18, No. 8, 08.2007, p. 1134-1145.

Research output: Contribution to journalArticle

@article{2b44ce8275ff4359bead5e3eb6b3d3dd,
title = "A fine-grained reputation system for reliable service selection in peer-to-peer networks",
abstract = "Distributed peer-to-peer (P2P) applications have been gaining momentum recently. In such applications, all participants are equal peers simultaneously functioning as both clients and servers to each other. A fundamental problem is, therefore, how to select reliable servers from a vast candidate pool. To answer this important open question, we present a novel reputation system built upon the multivariate Bayesian inference theory. Our system offers a theoretically sound basis for clients to predict the reliability of candidate servers based on self-experiences and feedbacks from peers. In our system, a fine-grained quality of service (QoS) differentiation method is designed to satisfy the diverse QoS needs of individual nodes. Our reputation system is also application-independent and can simultaneously serve unlimited P2P applications of different type. Moreover, it is semi-distributed in the sense that all applicationrelated QoS information is stored across system users either in a random fashion or through a distributed hash table (DHT). In addition, we propose to leverage credits and social awareness as reliable means of seeking honest feedbacks. Furthermore, our reputation system well protects the privacy of users offering feedbacks and is secure against various attacks such as defaming, flattering, and the Sybil attack. We confirm the effectiveness and efficiency of the propose system by extensive simulation results.",
keywords = "DHT, P2P, QoS, Reliability, Reputation, Security",
author = "Yanchao Zhang and Yuguang Fang",
year = "2007",
month = "8",
doi = "10.1109/TPDS.2007.1043",
language = "English (US)",
volume = "18",
pages = "1134--1145",
journal = "IEEE Transactions on Parallel and Distributed Systems",
issn = "1045-9219",
publisher = "IEEE Computer Society",
number = "8",

}

TY - JOUR

T1 - A fine-grained reputation system for reliable service selection in peer-to-peer networks

AU - Zhang, Yanchao

AU - Fang, Yuguang

PY - 2007/8

Y1 - 2007/8

N2 - Distributed peer-to-peer (P2P) applications have been gaining momentum recently. In such applications, all participants are equal peers simultaneously functioning as both clients and servers to each other. A fundamental problem is, therefore, how to select reliable servers from a vast candidate pool. To answer this important open question, we present a novel reputation system built upon the multivariate Bayesian inference theory. Our system offers a theoretically sound basis for clients to predict the reliability of candidate servers based on self-experiences and feedbacks from peers. In our system, a fine-grained quality of service (QoS) differentiation method is designed to satisfy the diverse QoS needs of individual nodes. Our reputation system is also application-independent and can simultaneously serve unlimited P2P applications of different type. Moreover, it is semi-distributed in the sense that all applicationrelated QoS information is stored across system users either in a random fashion or through a distributed hash table (DHT). In addition, we propose to leverage credits and social awareness as reliable means of seeking honest feedbacks. Furthermore, our reputation system well protects the privacy of users offering feedbacks and is secure against various attacks such as defaming, flattering, and the Sybil attack. We confirm the effectiveness and efficiency of the propose system by extensive simulation results.

AB - Distributed peer-to-peer (P2P) applications have been gaining momentum recently. In such applications, all participants are equal peers simultaneously functioning as both clients and servers to each other. A fundamental problem is, therefore, how to select reliable servers from a vast candidate pool. To answer this important open question, we present a novel reputation system built upon the multivariate Bayesian inference theory. Our system offers a theoretically sound basis for clients to predict the reliability of candidate servers based on self-experiences and feedbacks from peers. In our system, a fine-grained quality of service (QoS) differentiation method is designed to satisfy the diverse QoS needs of individual nodes. Our reputation system is also application-independent and can simultaneously serve unlimited P2P applications of different type. Moreover, it is semi-distributed in the sense that all applicationrelated QoS information is stored across system users either in a random fashion or through a distributed hash table (DHT). In addition, we propose to leverage credits and social awareness as reliable means of seeking honest feedbacks. Furthermore, our reputation system well protects the privacy of users offering feedbacks and is secure against various attacks such as defaming, flattering, and the Sybil attack. We confirm the effectiveness and efficiency of the propose system by extensive simulation results.

KW - DHT

KW - P2P

KW - QoS

KW - Reliability

KW - Reputation

KW - Security

UR - http://www.scopus.com/inward/record.url?scp=34548211355&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34548211355&partnerID=8YFLogxK

U2 - 10.1109/TPDS.2007.1043

DO - 10.1109/TPDS.2007.1043

M3 - Article

AN - SCOPUS:34548211355

VL - 18

SP - 1134

EP - 1145

JO - IEEE Transactions on Parallel and Distributed Systems

JF - IEEE Transactions on Parallel and Distributed Systems

SN - 1045-9219

IS - 8

ER -