About Open Access
[PhD Thesis] Choosing Reputable Resources in Unstructured Peer-to-Peer Networks using Trust Overlays
Lookup NU author(s)
Dr Georgios Pitsilis
Full text is not currently available for this publication.
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.
School of Computing Science, University of Newcastle upon Tyne
Newcastle upon Tyne
Newcastle University Library, NE2 4HQ, United Kingdom. Tel: 0044 (191) 222 7657
©2016 Newcastle University Library