Abstract
Reputation and trust are dominant challenges in peer-to-peer (P2P) networks in general and peer-to-peer sensor network (P2PWSN) in particular. Numerous efforts have been devoted to developing reputation management systems that can alleviate the difficulties in finding trustworthy communication partners in P2P networks. There are two main approaches in this field: peer-based reputation systems and message-based reputation systems, each of which has its own advantages and limitations. In this paper, we propose a new reputation system for P2PWSN, AuthenticPeer, which utilizes techniques from both approaches in a way that maximizes their advantages and overcomes their limitations. The proposed system has been tested thoroughly in various simulated P2PWSN environments under various number of files and common threat models. Experimental results illustrate enhanced performance of AuthenticPeer reputation system when compared to two P2P reputation systems, EigenTrust and Incremental EigenTrust, in terms of success rate of good users and fraction of inauthentic downloads, specifically with the threat models: individual malicious, malicious collective, camouflaged collective, and malicious spies, regardless of the number of files in the networks.
Highlights
Peer-to-peer sensor network (P2PWSN) is an emerging type of both wireless sensor networks and peer-to-peer (P2P) networks
P2P networks are appropriate for high-end communication nodes; they are well suited for flexible file sharing, content delivery, and distributed computing [2]
Since this paper intended to use the EigenTrust Algorithm as a baseline of its implementation, a comparison between peer-based reputation management systems built on EigenTrust and message-based reputation systems is summarized in Table 1, for quick review
Summary
Peer-to-peer sensor network (P2PWSN) is an emerging type of both wireless sensor networks and peer-to-peer (P2P) networks. In message-based reputation systems, the selection of a download source is based on the quality of the file instead of the quality of the peer. In this approach, certain parameters are calculated for each file through several transactions before it can be identified as a trustworthy or untrustworthy file.
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