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|Citation||PhD Thesis, Stanford University, 2005
The increasing availability of high bandwidth Internet connections and low-cost, commodity computers in people's homes has stimulated the use of resource sharing peerto- peer networks. These systems employ scalable mechanisms that allow anyone to offer content and services to other system users. However, the open accessibility of these systems make them vulnerable to malicious users wishing to poison the system with corrupted data or harmful services and worms. Because of this danger, users must be wary of the quality or validity of the resources they access. To mitigate the adverse behavior of unreliable or malicious peers in a network, researchers have suggested using reputation systems. Yet our understanding of how to incorporate an effective reputation system into an autonomous network is limited. This thesis categorizes and evaluates the components and mechanisms necessary to build robust, effective reputation systems for use in decentralized autonomous networks. Borrowing techniques from game theory and economic analysis, we begin with high-level models in order to understand general trends and properties of reputation systems and their effect on a user's behavior and experience. We then closely examine the effects of limited reputation sharing through simulations based on largescale measurements from actual, operating P2P networks. Finally, we propose new mechanisms for improving message routing throughput in decentralized networks of untrusted peers: one geared towards structured DHTs (SPROUT) and two other complementary mechanisms for mobile ad hoc networks (Watchdog and Pathrater).
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