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A holistic mechanism against file pollution in peer-to-peer networks
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Symposium on Applied Computing archive
Proceedings of the 2009 ACM symposium on Applied Computing table of contents
Honolulu, Hawaii
SESSION: Computer networks track table of contents
Pages 28-34  
Year of Publication: 2009
ISBN:978-1-60558-166-8
Authors
Zhuhua Cai  Peking University, Ministry of Education, China
Ruichuan Chen  Peking University, Ministry of Education, China
Jianqiao Feng  Peking University, Ministry of Education, China
Cong Tang  Peking University, Ministry of Education, China
Zhong Chen  Peking University, Ministry of Education, China
Jianbin Hu  Peking University, Ministry of Education, China
Sponsor
SIGAPP: ACM Special Interest Group on Applied Computing
Publisher
ACM  New York, NY, USA
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ABSTRACT

Content pollution is pervasive in the current peer-to-peer file sharing systems. Many previous reputation models have been proposed to address this problem, however, such models strongly rely on the participants' feedback.

In this paper, we bring forward a new holistic mechanism which integrates the reputation model, inherent file-source-based information and the statistical data reflecting the diffusion state to defend against pollution attack. First, we deploy a redundancy mechanism to assure that the file requester receives the correct indices that accord with the information published by the file provider. Second, we complement the reputation information with the diffusion data to help the file requester select the authentic file for downloading. Finally, we introduce a block-oriented probabilistic verification protocol to help the file requester discern the polluted files during the downloading with a low cost.

We perform a simulation which shows that our holistic mechanism can perform very well and converge to a high accuracy rapidly, even in a highly malicious environment.


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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Cachelogic: The picture of p2p file sharing, http://www.cachelogic.com/research.
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Collaborative Colleagues:
Zhuhua Cai: colleagues
Ruichuan Chen: colleagues
Jianqiao Feng: colleagues
Cong Tang: colleagues
Zhong Chen: colleagues
Jianbin Hu: colleagues