Securing Peer-to-Peer Content Sharing Systems through Detecting Pollution Behaviors

Abstract

Peer-to-Peer (P2P) content sharing systems have experienced an explosive growth, and now dominate large fractions of both the Internet users and traffic volume. However, due to the self-organization and self-maintenance nature of P2P overlay networks, these systems are vulnerable to the content pollution, where attackers aggressively inject a large quantity of polluted content into the systems. Such polluted content could largely reduce the availability of the original authentic content, thus enormously shattering genuine users' confidence in the P2P content sharing systems.

In this report, we present a survey and comparison of various models on defending against content pollution. We categorize the various schemes into some groups and discuss the application-level model performance of each group. At end of the report, we present some future aspects on defending against content pollution; moreover, some important and useful evaluation results are in the report.