Identity Systematizing Conviction Model For Peer To Peer Systems

Abstract

Open nature of peer-to-peer systems exposes them to malicious activity. Building trust relationships among peers can mitigate attacks of malicious peers. Peer to peer network is decentralized and distributed network, which is useful for file sharing via internet. Due to malicious activity, still it is insecure during file sharing. Depending on the past interaction and their recommendation, trustworthiness of a peer can be build. In order to measure the trustworthiness, two constraints are considered namely, services and recommendations. Peer to peer is an advanced computer networking where all computers contribute to equivalent task for processing data. A Peer to peer network can be an ad hoc connection in which a pair of computers attached by means of a universal serial bus to transmit files. Security is not much effective in this type of systems it is because if the connections are not fixed to the computers appropriately then there will be difficulty in accessing certain files and the relationship is untrusted. Hence security in peer to peer systems is complex since disputes are created by lack of integrated authority. This paper presents distributed algorithms that enable a peer to reason about trustworthiness of other peers based on past interactions and recommendations. Peers create their own trust network in their proximity by using local information available and do not try to learn global trust information. Two contexts of trust, service, and recommendation contexts, are defined to measure trustworthiness in providing services and giving recommendations.