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
Improved Result Ranking in P2P File-Sharing Systems by Probing for Metadata
NCA '06 Proceedings of the Fifth IEEE International Symposium on Network Computing and Applications
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
Spam characterization and detection in peer-to-peer file-sharing systems
Proceedings of the 17th ACM conference on Information and knowledge management
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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 propose probing technique to collect more complete feature information of query results from the network and apply feature-based ranking for automatically detecting spam in P2P query result sets. Furthermore, we examine the tradeoff between the spam detection performance and the network cost. Different ways of probing are explored to reduce the network cost. 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 with reasonable cost.