Study Of Evolutive Reputation System And Its Key Techniques In Peer-to-Peer Environment

Currently,the security and availability problems of Peer-to-Peer(P2P) systems are becoming one of the biggest obstacles which Constraint the development and application of P2P technology, as there are lots of malicious and selfish behavior here, the trust risk for P2P is now rapidly increasing. In order to build a smooth running, secure and efficient network environment for P2P systems, the reputation system provides an effective mechanism, which can inhibit the peers' malicious behavior, and incent them to actively participate into the transaction.In order to make the reputation system to adapt to the evolution of P2P systems, and can still ensure and improve its effectiveness in complex dynamic environment, and ultimately promotes the anagenesis of P2P systems. In view of this, under the background of P2P file sharing system, and on the basis of in-depth analyzing of the evolution of P2P systems, and with the current theoretical achievements and shortcomings, two closely related research questions are proposed in our thesis: how to build a more natural and more reasonable trust evaluating model; and how to adaptively regulate the parameter and structure of trust evaluating model. To solve those questions above, our work in this paper can be briefly introduced as following.(1)An Evolutive Reputation System and its FrameworkIn view of the similarity between P2P systems and ecosystem, and by using the related theories of Network Society and Ecology for reference, the concept of P2P social ecosystem (P2PSE) is proposed, where this paper presents an evolutive reputation system (ERS) based on hybrid architecture with the characteristics of "distributed in the whole, whereas distributed in the cluster".(2) A Population Anagenesis based Trust Cognition ModelAs the trust relationship between peers in P2P system to some extent reflects the interpersonal trust relationship in human society, and the build and maintenance of interpersonal trust is an evolutive cognitive process. In view of this, through thinking out of the traditional modeling for trust evaluating, and being inspired by the population anagenesis of ecological systems, and being associated with social cognitive theory and related method, a population anagenesis based trust cognition model (PATrust) is proposed. The main contributions of the PATrust include: good cognitive habits and rich cognitive experience of human beings are effectively utilized; three evolutionary strategies, i.e. selection, crossover and mutation are introduced so as to effectively cognize the peer's trust; in order to reduce the subjectivity of the calculating of transaction satisfaction degree (TSD), a model for calculating TSD based on "practise what you preach" is proposed; through introducing the mechanism of collaborative filtering for recommendations, the Efficiency and accuracy of recommendation filtering and the recommending trust value evaluating are greatly improved.Our experiments show that the PATrust outperforms the traditional trust evaluating model, such as the EigenTrust and P2PRep, in terms of both Convergence and total fitness degree, and that our model can more effectively inhibit a broader type of malicious behavior, especially the attack behavior performed by some adaptable malicious peers.(3)A Metacognition-based Adaptive Regulating Model for the parameter of PATrustIn order to improve the adaptability of trust evaluating model, some existing models commonly utilize approaches by introducing the deterministic parameters, however, those approaches still have problems, such as: the rationality of parameter setting needs to validate; it's hard to dynamically adjust the parameters at runtime. As a result, from the perspective of cognitive regulation and fuzzy logic control, and through using the good habits and rich experience of human beings in cognitive regulation, a metacognition-based adaptive regulating model for the parameter of PATrust (MARM) is proposed.Our experiments show that the PATrust with MARM outperforms the PATrust without MARM in dynamic environment.(4) A Cluster-based Adaptive Regulating Model for the structure of PATrust Most existing distributed architecture-based trust evaluating models have limitation in the complexity, the cost of communication, storage and computation, and the convergence of trust value. Furthermore, the trust evaluating models based on hybrid architecture with characteristics of "distributed in the whole, whereas centralized in the cluster" also have their limitation. We propose a cluster-based trust cognitive model (CBTrust). Through the interaction between the cluster-based trust cognition and centripetal force-based Cluster Evolution Management, the main contributions of the CBTrust include: the performance of trust cognitive model is improved; good incentive effect for peers is also obtained.Our experiments show that the performance of the CBTrust is greatly improved while comparing with the PATrust, and the CBTrust can effectively incent the peers to actively participate into the transaction, and the CBTrust is robust to resist the attack aimed at the CBTrust itself.