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Lookup NU author(s): Dr Georgios Pitsilis
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. Reputation and Recommender systems have existed for years but usually as 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.
Author(s): Pitsilis GK
Publication type: Report
Publication status: Published
Series Title: School of Computing Science Technical Report Series
Year: 2008
Pages: 177
Print publication date: 01/02/2008
Source Publication Date: February 2008
Report Number: 1070
Institution: School of Computing Science, University of Newcastle upon Tyne
Place Published: Newcastle upon Tyne
URL: http://www.cs.ncl.ac.uk/publications/trs/papers/1070.pdf
