Because of the anonymity that P2P networks provide, they are an ideal medium for the exchange of contraband material such as child pornography. Unfortunately, not much research has been conducted on how to best monitor these types of networks for contraband searching and sharing activity. This thesis proposes techniques to advance the state of the art in peer to peer data exchange monitoring and detection of nodes that participate in distributing and sharing contraband material.

Because of the legal considerations in working with a live P2P network and the technical difficulty in developing and testing a "surveillance" system for P2P networks, a simulator was developed that attempts to accurately simulate the behavior of users on P2P networks based upon empirical data collected from several researchers.

With the help of the simulation platform that has been developed, a complete methodology for monitoring "contraband" activity and reporting the most prolific contraband users has been created. This methodology, if implemented on an actual P2P network, should allow the detection of members of the network who are the most active sharers and distributors of contraband material.