Security Framework Based on Reputation Mechanism for Peer-To-Peer Systems

Peer-to-peer networks have emerged over the past several years as a new and effective way for distributed resources to communicate and cooperate. Peer-to-peer computing is the sharing of computer resources and services by direct system exchange. These information sharing environments are increasi...

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Bibliographic Details
Main Author: Sinnanaidu, Subba Rao
Format: Thesis
Language:English
English
Published: 2004
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/101/1/548981_FK_2004_12.pdf
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Summary:Peer-to-peer networks have emerged over the past several years as a new and effective way for distributed resources to communicate and cooperate. Peer-to-peer computing is the sharing of computer resources and services by direct system exchange. These information sharing environments are increasingly gaining acceptance on the Internet as they provide an infrastructure in which the desired information can be located and downloaded while preserving the anonymity. Some of the peer-to-peer networks such as Napster and Gnutella which support anonymity, open doors to possible misuse and abuse of the network resources. This is apparent in the spread of tampered resources, malicious program such as Trojan Horses and viruses by resource provider itself. In this thesis, a Peer Security Framework (PSF) has been developed using reputation-based mechanism to address these problems. This is done by an approach where the servents can keep track and share the information about the reputation of their peers with other peers. The “reputation sharing” based on a distributed polling iv algorithm in which the resource requestors can assess the reliability of respective provider before initiating the download. This approach nicely complements the existing peer-to-peer protocols and gives a limited disruption on current implementations. Furthermore, it maintains the current level of anonymity of requestors and providers as well as that of the parties sharing their views on other’s reputations.