4 research outputs found

    Choosing reputable resources in unstructured peer-to-peer networks using trust overlays

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    In recent years Peer-to-Peer Systems have gained popularity, and are best known as a convenient way of sharing content. However, even though they have existed for a considerable length of time, no method has yet been developed to measure the quality of the service they provide nor to identify cases of misbehaviour by individual peers. This thesis attempts to give to P2P systems some quality measures with the potential of giving querying peers criteria by which to judge and make predictions about the behaviour of their counterparts. The work includes the design of a reputation system from which querying peers can seek guidance before they commit to transaction with another peer. but usually as Reputation and Recommender systems have existed for years centralized services. Our innovation is the use of a distributed recommendation system which will be supported by the peers themselves. The system operates in the same manner as "word-of-mouth" in human societies does. In contrast to other reputation systems the word-of-mouth technique is itself decentralized since there is no need for central entities to exist as long as there are participants willing to be involved in the recommendation process. In order for a society to exist it is necessary that members have some way of knowing each other so that they can form relationships. The main element used to link members in an online community together is a virtual trust relationship that can be identified from the evidence that exists about their virtual partnerships. In our work we approximate the level of trust that could exist between any two parties by exploiting their similarity, constructing a network that is known as "web of trust". Using the transitivity property of trust, we make it possible for more peers to come in to contact through virtual trust relationships and thus get better results than in an ordinary system.EThOS - Electronic Theses Online ServiceGreek State Scholarships FoundationGBUnited Kingdo

    Trust-aware information retrieval in peer-to-peer environments

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    Information Retrieval in P2P environments (P2PIR) has become an active field of research due to the observation that P2P architectures have the potential to become as appealing as traditional centralised architectures. P2P networks are formed with voluntary peers that exchange information and accomplish various tasks. Some of them may be malicious peers spreading untrustworthy resources. However, existing P2PIR systems only focus on finding relevant documents, while trustworthiness of documents and document providers has been ignored. Without prior experience and knowledge about the network, users run the risk to review,download and use untrustworthy documents, even if these documents are relevant. The work presented in this dissertation provide the first integrated framework for trust-aware Information Retrieval in P2P environments, which can retrieve not only relevant but also trustworthy documents. The proposed content trust models extend an existing P2P trust management system, PeerTrust, in the context of P2PIR to compute the trust values of documents and document providers for given queries. A method is proposed to estimate global term statistics which are integrated with existing relevance-based approaches for document ranking and peer selection. Different approaches are explored to find optimal parametersettings in the proposed trust-aware P2PIR systems. Moreover, system architectures and data management protocols are designed to implement the proposed trust-aware P2PIR systems in structured P2P networks. The experimental evaluation demonstrates that P2PIR can benefit from trust-aware P2PIR systems significantly. It can importantly reduce the possibility of untrustworthy documents in the top-ranked result list. The proposed estimated global term statistics can provide acceptable and competitive retrieval accuracy within different P2PIR scenarios.EThOS - Electronic Theses Online ServiceORSSchool ScholarshipGBUnited Kingdo

    Evaluation criteria for trust models with specific reference to prejudice filters

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    The rapid growth of the Internet has resulted in the desperate need for alternative ways to keep electronic transactions secure while at the same time allowing entities that do not know each other to interact. This has, in turn, led to a wide area of interest in the issues of trust and trust modeling to be used by machines. A large amount of work has already been undertaken in this area in an attempt to transfer the trust and interaction decision making processes onto the machine. However this work has taken a number of different approaches with little to no correlation between various models and no standard set of criteria was even proposed that can be used to evaluate the value of such models. The proposed research chooses to use a detailed literature survey to investigate the current models in existence. This investigation focuses on identifying criteria that are required by trust models. These criteria are grouped into four categories that represent four important concepts to be implemented in some manner by trust models: trust representation, initial trust, trust update and trust evaluation. The process of identifying these criteria has led to a second problem. The trust evaluation process is a detailed undertaking requiring a high processing overhead. This process can either result in a value that allows an agent to trust another to a certain extent or in a distrust value that results in termination of the interaction. The evaluation process required to obtain the distrust value is just as process intensive as the one resulting in determining a level of trust and the constraints that will be placed on an interaction. This raises the question: How do we simplify the trust evaluation process for agents that have a high probability of resulting in a distrust value? This research solves this problem by adding a fifth category to the criteria already identified; namely: prejudice filters. These filters have been identified by the literature study and are tested by means of a prototype implementation that uses a specific scenario in order to test two simulation case studies.Dissertation (MSc)--University of Pretoria, 2008.Computer Scienceunrestricte
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