Prevent Contents Leaking in P2P CDNs with Robust and Quick Detection of Colluders

Abstract

Abstract:The objective of Peer-to-Peer Content Delivery Networks is to deliver copyrighted contents to paid clients in an efficient and secure manner. To protect such contents from being distributed to unauthorized peers, Lou and Hwang proposed a proactive content poisoning scheme to restrain an illegal download conducted by unauthorized peers, and a scheme to identify colluders who illegally leak the contents to such unauthorized peers. In this paper, we propose three schemes which extend the Lou and Hwang's colluder detection scheme in two directions. The first direction is to introduce an intensive probing to check suspected peers, and the second direction is to adopt a reputation system to select reliable (non-colluder) peers as a decoy. The performance of the resulting scheme is evaluated by simulation. The result of simulations indicates that the proposed schemes detect all colluders about 30% earlier on average than the original scheme while keeping the accuracy of the colluder detection at medium collusion rate.

Reputation-Based Colluder Detection Schemes for Peer-to-Peer Content Delivery Networks

“…Thus, in order to apply P2P reputation systems to the colluder detection problem, we need to significantly increase the quality of colluder detection in such a way that it identifies almost all colluders without misidentifying non-colluder peers. In our previous paper [1], we introduced the notion of reputation to improve the quality of the decoy-based colluder detection scheme proposed by Lou and Hwang [10]. However, our previous scheme merely qualifies the peers to be selected as decoy and the qualification of other peers was remained open in our previous paper.…”