Asymptotic methods in statistical theory
Asymptotic methods in statistical theory
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Matrix analysis and applied linear algebra
Matrix analysis and applied linear algebra
ACM Transactions on Internet Technology (TOIT)
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
Propagation of trust and distrust
Proceedings of the 13th international conference on World Wide Web
PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities
IEEE Transactions on Knowledge and Data Engineering
Efficient pagerank approximation via graph aggregation
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
SeAl: Managing Accesses and Data in Peer-to-Peer Sharing Networks
P2P '04 Proceedings of the Fourth International Conference on Peer-to-Peer Computing
Trust Framework for P2P Networks Using Peer-Profile Based Anomaly Technique
ICDCSW '05 Proceedings of the Second International Workshop on Security in Distributed Computing Systems (SDCS) (ICDCSW'05) - Volume 02
MINERVA: collaborative P2P search
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Updating Markov Chains with an Eye on Google's PageRank
SIAM Journal on Matrix Analysis and Applications
A non-manipulable trust system based on EigenTrust
ACM SIGecom Exchanges
Peer-to-Peer Systems and Applications (Lecture Notes in Computer Science)
Peer-to-Peer Systems and Applications (Lecture Notes in Computer Science)
Proceedings of the 15th international conference on World Wide Web
Taxonomy of trust: categorizing P2P reputation systems
Computer Networks: The International Journal of Computer and Telecommunications Networking - Management in peer-to-peer systems
Estimating the global pagerank of web communities
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Computing pagerank in a distributed internet search system
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Predicting trusts among users of online communities: an epinions case study
Proceedings of the 9th ACM conference on Electronic commerce
Adversarial Information Retrieval on the Web (AIRWeb 2007)
ACM SIGIR Forum
Distortion as a validation criterion in the identification of suspicious reviews
Proceedings of the First Workshop on Social Media Analytics
Foundations and Trends in Information Retrieval
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Peer-to-peer (P2P) networks have received great attention for sharing and searching information in large user communities. The open and anonymous nature of P2P networks is one of its main strengths, but it also opens doors to manipulation of the information and of the quality ratings. In our previous work (J. X. Parreira, D. Donato, S. Michel and G. Weikum in VLDB 2006) we presented the JXP algorithm for distributed computing PageRank scores for information units (Web pages, sites, peers, social groups, etc.) within a link- or endorsement-based graph structure. The algorithm builds on local authority computations and bilateral peer meetings with exchanges of small data structures that are relevant for gradually learning about global properties and eventually converging towards global authority rankings. In the current paper we address the important issue of cheating peers that attempt to distort the global authority values, by providing manipulated data during the peer meetings. Our approach to this problem enhances JXP with statistical techniques for detecting suspicious behavior. Our method, coined Trust JXP, is again completely decentralized, and we demonstrate its viability and robustness in experiments with real Web data.