research-article

Defending online reputation systems against collaborative unfair raters through signal modeling and trust

Authors:

Yan Lindsay Sun,

Qing YangAuthors Info & Claims

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

Pages 1308 - 1315

https://doi.org/10.1145/1529282.1529575

Published: 08 March 2009 Publication History

Abstract

Online feedback-based rating systems are gaining popularity. Dealing with collaborative unfair ratings in such systems has been recognized as an important but difficult problem. This problem is challenging especially when the number of honest ratings is relatively small and unfair ratings can contribute to a significant portion of the overall ratings. In addition, the lack of unfair rating data from real human users is another obstacle toward realistic evaluation of defense mechanisms. In this paper, we propose a set of methods that jointly detect smart and collaborative unfair ratings based on signal modeling. Based on the detection, a framework of trust-assisted rating aggregation system is developed. Furthermore, we design and launch a Rating Challenge to collect unfair rating data from real human users. The proposed system is evaluated through simulations as well as experiments using real attack data. Compared with existing schemes, the proposed system can significantly reduce the impact from collaborative unfair ratings.

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Cited By

You XHou FChiclana F(2024)A reputation-based trust evaluation model in group decision-making frameworkInformation Fusion10.1016/j.inffus.2023.102082103(102082)Online publication date: Mar-2024
https://doi.org/10.1016/j.inffus.2023.102082
Xiao JZeng JMiao XCao YZhao JFeng Z(2023)USDSE: A Novel Method to Improve Service Reputation Based on Double-Side EvaluationMachine Learning for Cyber Security10.1007/978-3-031-20102-8_37(484-498)Online publication date: 13-Jan-2023
https://doi.org/10.1007/978-3-031-20102-8_37
Muller TWang DSun J(2020)Provably Robust Decisions based on Potentially Malicious Sources of Information2020 IEEE 33rd Computer Security Foundations Symposium (CSF)10.1109/CSF49147.2020.00036(411-424)Online publication date: Jun-2020
https://doi.org/10.1109/CSF49147.2020.00036
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Defending online reputation systems against collaborative unfair raters through signal modeling and trust

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cover image ACM Conferences

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

March 2009

2347 pages

ISBN:9781605581668

DOI:10.1145/1529282

Conference Chairs:
Sung Y. Shin
South Dakota State University, United States
,
Sascha Ossowski
University Rey Juan Carlos, Spain

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 March 2009

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SAC09: The 2009 ACM Symposium on Applied Computing

March 8, 2009 - March 12, 2008

Hawaii, Honolulu

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

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https://doi.org/10.1016/j.inffus.2023.102082
Xiao JZeng JMiao XCao YZhao JFeng Z(2023)USDSE: A Novel Method to Improve Service Reputation Based on Double-Side EvaluationMachine Learning for Cyber Security10.1007/978-3-031-20102-8_37(484-498)Online publication date: 13-Jan-2023
https://doi.org/10.1007/978-3-031-20102-8_37
Muller TWang DSun J(2020)Provably Robust Decisions based on Potentially Malicious Sources of Information2020 IEEE 33rd Computer Security Foundations Symposium (CSF)10.1109/CSF49147.2020.00036(411-424)Online publication date: Jun-2020
https://doi.org/10.1109/CSF49147.2020.00036
Abrardo ABarni MKallas KTondi BAbrardo ABarni MKallas KTondi B(2020)Security Attacks and Defenses in Distributed Sensor NetworksInformation Fusion in Distributed Sensor Networks with Byzantines10.1007/978-981-32-9001-3_3(29-43)Online publication date: 15-Jul-2020
https://doi.org/10.1007/978-981-32-9001-3_3
Wu CGerla Mvan der Schaar M(2017)Social Norm Incentives for Network Coding in ManetsIEEE/ACM Transactions on Networking10.1109/TNET.2017.265605925:3(1761-1774)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1109/TNET.2017.2656059
Kamhoua GPissinou NIyengar SBeltran JMiller JKamhoua CNjilla L(2017)Approach to detect non-adversarial overlapping collusion in crowdsourcing2017 IEEE 36th International Performance Computing and Communications Conference (IPCCC)10.1109/PCCC.2017.8280462(1-8)Online publication date: Dec-2017
https://doi.org/10.1109/PCCC.2017.8280462
Cao LSun YWang SLi M(2016)Detecting Malicious Behavior and Collusion for Online Rating System2016 IEEE Trustcom/BigDataSE/ISPA10.1109/TrustCom.2016.0174(1046-1053)Online publication date: Aug-2016
https://doi.org/10.1109/TrustCom.2016.0174
Shen HLin YSapra KLi Z(2016)Enhancing Collusion Resilience in Reputation SystemsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2015.248919827:8(2274-2287)Online publication date: 1-Aug-2016
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Cuomo SDe Michele PGalletti APonti G(2016)A Numerical Approach for Assigning a Reputation to Users of an IoT FrameworkProcedia Computer Science10.1016/j.procs.2016.09.07398:C(455-460)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.procs.2016.09.073
Ghachem M(2016)The institution as a blunt instrument: Cooperation through imperfect observabilityJournal of Theoretical Biology10.1016/j.jtbi.2016.02.013396(182-190)Online publication date: May-2016
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