The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
Information Retrieval: Algorithms and Heuristics (The Kluwer International Series on Information Retrieval)
Content availability, pollution and poisoning in file sharing peer-to-peer networks
Proceedings of the 6th ACM conference on Electronic commerce
Denial-of-service resilience in peer-to-peer file sharing systems
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
MailRank: using ranking for spam detection
Proceedings of the 14th ACM international conference on Information and knowledge management
Detecting spam web pages through content analysis
Proceedings of the 15th international conference on World Wide Web
Malware prevalence in the KaZaA file-sharing network
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Improving web spam classification using rank-time features
AIRWeb '07 Proceedings of the 3rd international workshop on Adversarial information retrieval on the web
Improving web spam classifiers using link structure
AIRWeb '07 Proceedings of the 3rd international workshop on Adversarial information retrieval on the web
Experience with an object reputation system for peer-to-peer filesharing
NSDI'06 Proceedings of the 3rd conference on Networked Systems Design & Implementation - Volume 3
Countering web spam with credibility-based link analysis
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
Distributed, Automatic File Description Tuning in Peer-to-Peer File-Sharing Systems
P2P '07 Proceedings of the Seventh IEEE International Conference on Peer-to-Peer Computing
Cost-effective spam detection in p2p file-sharing systems
Proceedings of the 2008 ACM workshop on Large-Scale distributed systems for information retrieval
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Spam is highly pervasive in P2P file-sharing systems and is difficult to detect automatically before actually downloading a file due to the insufficient and biased description of a file returned to a client as a query result. To alleviate this problem, we first characterize spam and spammers in the P2P file-sharing environment and then describe feature-based techniques for automatically detecting spam in P2P query result sets. Experimental results show that the proposed techniques successfully decrease the amount of spam by 9% in the top-200 results and by 92% in the top-20 results.