Secure and Privacy- Aware Searching in Peer-to-Peer Networks

TL;DR

This paper introduces a trust management scheme for peer-to-peer networks that enhances search efficiency, scalability, and user privacy by forming trusted peer overlays and exploiting semantic community structures.

Contribution

It proposes a novel topology adaptation method that constructs trusted peer overlays, improving search efficiency and privacy protection in P2P networks.

Findings

Efficient search for trustworthy peers demonstrated through simulations.

Malicious peers experience increased search times, deterring malicious activities.

Enhanced privacy protection for user activity patterns.

Abstract

The existing peer-to-peer networks have several problems such as fake content distribution, free riding, white-washing and poor search scalability, lack of a robust trust model and absence of user privacy protection mechanism. Although, several trust management and semantic community-based mechanisms for combating free riding and distribution of malicious contents have been proposed by some researchers, most of these schemes lack scalability due to their high computational, communication and storage overhead. This paper presents a robust trust management scheme for P2P networks that utilizes topology adaptation by constructing an overlay of trusted peers where the neighbors are selected based on their trust ratings and content similarities. While increasing the search efficiency by intelligently exploiting the formation of semantic community structures by topology adaptation among the trustworthy peers, the scheme provides the users a very high level of privacy protection of their usage and consumption patterns of network resources. Simulation results demonstrate that the proposed scheme provides efficient searching to good peers while penalizing the malicious peers by increasing their search times as the network topology stabilizes.