Trust Metrics Evaluation for Peer-to-Peer Systems

P2P system is a self-organizing system of equal, autonomous peers which aims for the shared usage of distributed resources in a networked environment avoiding central services. P2P system depends on the collaboration of peers to complete a task. In order to establish trustworthiness among the peers in the system, various trust metrics are evaluated. Based on the metric values the peers are categorized as either trustworthy or untrustworthy. The general structure of P2P system is depicted in the Fig 1. The metrics are evaluated in two contexts: based on the interaction that happens between the peers and based on the feedback that is collected from the peers with whom the interaction happened. In client server architecture the trust information’s collected from various peers are stored and managed securely whereas in P2P systems the peers collaborate among themselves and store the trust information [8], [4]. In P2P systems any peer may request for a service from its neighbouring peers in the network, but the service provider may either be malicious or may act as good peer in providing the service. Sometimes the malicious peer may serve as an individual attacker, which exhibits various behaviours like: naive, discriminatory, hypocritical and oscillatory [12]. The naive peers always upload the infected file for its service requestor, whereas a discriminatory peer selects a group of victims and uploads the infected file only for those peers. A hypocritical and oscillatory peer behaves alike, because for a certain period of time they may be malicious and for the rest of the time they behave as good peers. In this paper we propose a trust model that reduces the maliciousness in the P2P system. By evaluating various trust metric values the peers in the system can be ranked accordingly, based on which the peers for future interaction are chosen. The peer tries to collect only the local trust information from its neighbouring peers, by which the trust model is developed within its proximity or area. Initially the peers in the system are strangers to each other, but once the service (either uploading or downloading) [13] has been provided they become acquaintance. The interaction and recommendation are measured based on three parameters: satisfaction, importance and fading effect. Satisfaction measures how much the interaction fulfilled the needs of the service requestor. Importance is measured based on the weight age given to the interaction. If any new interaction happens between the peers the old interaction loses its importance, this issue is addressed by the fading effect parameter. The trust model defines three important metrics: service, recommendation and reputation. Service trust metric is essential when evaluating the trustworthiness of the acquaintance. The Service trust metric value is essential while selecting the best service provider for interaction process. Recommendation and reputation are needed while measuring the trustworthiness of the stranger. Recommendation trust metric is measured as a result of collecting recommendation from various acquaintance peers Reputation metric is needed mainly in the initial stage of interaction as the stranger’s probability will be high; while the experience with the acquaintance peer increases automatically the reputation loses its importance [1] [5]. The remainder of this paper is organized as follows: Section 2 discusses the related research. Section 3 explains the peer-to-peer file sharing process. Section 4 presents the analysis of the results. Section 5 summarizes the results and future work.