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Chapter 9 EigenTrust > 9.3 EigenTrust - Pg. 86

86 CHAPTER 9 We show that the idea of transitive trust leads to a system where global trust val- ues correspond to the left principal eigenvector of a matrix of normalized local trust values (just as in PageRank). We show how to perform this eigenvector computation in a distributed manner with just a few lines of code, where the message complex- ity is provably bounded and empirically low. Most important, we show that this system is highly effective in decreasing the number of unsatisfactory downloads, even when up to 70% of the peers in the network form a malicious collective in an attempt to subvert the system. 9.3 EIGENTRUST In this section, we describe the EigenTrust algorithm. In EigenTrust, the global rep- utation of each peer i is given by the local trust values assigned to peer i by other peers, weighted by the global reputations of the assigning peers. In Section 9.3.1, we show how to normalize the local trust values in a manner that leads to an el- egant probabilistic interpretation and an efficient algorithm for aggregating these values. In Section 9.3.2, we discuss how to aggregate the normalized trust values in a sensible manner. In Section 9.3.3, we discuss the probabilistic interpretation of the local and global trust values. In Sections 9.3.4­9.3.6, we present an algorithm for computing the global trust values.