Date of Award
Doctor of Philosophy (PhD)
Engineering and Public Policy
John M. Peha
Lorrie Faith Cranor
Michael D. Smith
This research uses data collected from a university campus network via Deep Packet Inspection (DPI) monitoring and from the largest public BitTorrent tracker to characterize the extent of unauthorized transfers of copyrighted content using Peer-to-Peer (P2P) and to evaluate the effectiveness and limitations of DPI in detection of such activity, both to provide a perspective of how much copyright infringement happens using P2P and to inform those seeking to deploy DPI technology.
Use of P2P and transfers of copyrighted content were widespread on campus. In Spring 2008, 40% of students living on campus were detected using a P2P protocol, 70% of which were observed attempting to transfer copyrighted material. In late 2010, we estimate that over 800 million copies of content were transferred globally using BitTorrent per day, with an estimated number of transferred songs 13.1 times greater than worldwide sales of songs, and estimated number of transferred movies 6.8 times greater than worldwide box-office sales and 16.4 times greater than U.S. DVD and Blu-ray sales. Most transfers were from a small number of very popular titles that were widely available for sale. We found no evidence that use of P2P to transfer content without violating copyright was common both on campus and global BitTorrent. This indicates that copyright law is violated frequently using P2P, and while we cannot quantify how P2P transfers translate to lost sales, it is reasonable to assume some sales are lost due to P2P.
Focusing on effectiveness of DPI, after a couple weeks of monitoring DPI found up to 80% of detected P2P users attempting to transfer copyrighted content. In the short term, DPI could be effective to assess which network users transfer copyrighted content using P2P given some weeks of monitoring. However, limitations such as not being able to detect users of encrypted P2P can reduce DPIʼs effectiveness in the long term. Using behavioral classifiers that we implemented and that can detect encrypted BitTorrent from traffic summaries, we found students shifting from unencrypted to encrypted BitTorrent in the 2007-2008 academic year. If this trend continues, effectiveness of DPI for enforcement can be significantly hindered
Mateus, Alexandre M., "Copyright Violation on the Internet: Extent and Approaches to Detection and Deterrence" (2011). Dissertations. Paper 50.