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TrustGuard: countering vulnerabilities in reputation management for decentralized overlay networks
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Source International World Wide Web Conference archive
Proceedings of the 14th international conference on World Wide Web table of contents
Chiba, Japan
SESSION: Trustworthy Web sites table of contents
Pages: 422 - 431  
Year of Publication: 2005
ISBN:1-59593-046-9
Authors
Mudhakar Srivatsa  Georgia Institute of Technology, Atlanta, GA
Li Xiong  Georgia Institute of Technology, Atlanta, GA
Ling Liu  Georgia Institute of Technology, Atlanta, GA
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 8,   Downloads (12 Months): 81,   Citation Count: 22
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ABSTRACT

Reputation systems have been popular in estimating the trustworthiness and predicting the future behavior of nodes in a large-scale distributed system where nodes may transact with one another without prior knowledge or experience. One of the fundamental challenges in distributed reputation management is to understand vulnerabilities and develop mechanisms that can minimize the potential damages to a system by malicious nodes. In this paper, we identify three vulnerabilities that are detrimental to decentralized reputation management and propose TrustGuard - a safeguard framework for providing a highly dependable and yet efficient reputation system. First, we provide a dependable trust model and a set of formal methods to handle strategic malicious nodes that continuously change their behavior to gain unfair advantages in the system. Second, a transaction based reputation system must cope with the vulnerability that malicious nodes may misuse the system by flooding feedbacks with fake transactions. Third, but not least, we identify the importance of filtering out dishonest feedbacks when computing reputation-based trust of a node, including the feedbacks filed by malicious nodes through collusion. Our experiments show that, comparing with existing reputation systems, our framework is highly dependable and effective in countering malicious nodes regarding strategic oscillating behavior, flooding malevolent feedbacks with fake transactions, and dishonest feedbacks.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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C. Dellarocas. Sanctioning reputation mechanisms in online trading environments with moral hazard. In MIT Sloan Working Paper No. 4297-03, 2004.
 
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M. Richardson, R. Agarwal, and P. Domingos. Trust management for the semantic web. In Proceedings of International Semantic Web Conference, 2003.
 
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CITED BY  22

Collaborative Colleagues:
Mudhakar Srivatsa: colleagues
Li Xiong: colleagues
Ling Liu: colleagues