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A Trust Model Based On Node's Capability And Quality For P2P Networks

Posted on:2010-08-31Degree:MasterType:Thesis
Country:ChinaCandidate:D D SunFull Text:PDF
GTID:2178360302461807Subject:Computer software and theory
Abstract/Summary:PDF Full Text Request
P2P network is peer-to-peer, there is no central node, and each node provides the resources to other nodes, at the same time it can share resources provided by other nodes. P2P networks are dynamic, open and anonymous. Because of its anonymity, a number of nodes based on their own rational considerations only share the resources provided by others, or provide false information. We need to use a certainly incentive mechanism and set up the trust model to resolve this problem proposed above.With the rapid development of P2P networks, the problem of trustless between nodes is becoming increasingly serious. We set up the trust model to resolve this problem. Trust model computes the trust degree of the nodes through specific algorithm, and interact with the node whose trust degree is highest. When the interaction is complete, the model uses the incentive mechanism to give the node evaluation which will be used as the source data in the next calculation to the trust degree.In existing P2P network trust models, the evaluation offered by applicant is always relatively simple, so there is lack of prior information in computing the trust value, which would weak the rationality and objectivity of P2P model. To solve this problem, this paper proposes a novel trust model which is based on node's capacity and quality. Through the definition of capacity and quality, we propose multi-dimensional evaluation vectors with which we induce the method of computing the trust value and give the determine algorithm to malicious nodes. Simulation and analysis show that our novel model can provide effective trust services and is eligible to resist and distinguish the malicious nodes which are characterized by attack, conspiracy and strategy.
Keywords/Search Tags:Trust Model, Evaluation Vectors, Prior Information, Capability, Quality
PDF Full Text Request
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