Anir-networking07.pdf
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In an e ort to prosecute P2P users, RIAA and MPAA have eportedly started to create decoy users: they participate in P2P networks in order to identify illegal sharing of content. This has reportedly scared some users who are afraid of being caught. The question we attempt to answer is how prevalent is this phenomenon: how likely is it that a user will run into such a \fake user" and thus run the risk of a lawsuit? The rst challenge is identifying these \fake users". We collect this information from a number of free open source software projects which are trying to identify such IP address ranges by forming the so-called blocklists. The second challenge is running a large scale experiment in order to obtain reliable and diverse statistics. Using Planetlab, we conduct active measurements, spanning a period of 90 days, from January to March 2006, spread over 3 continents. Analyzing over a 100 GB of TCP header data, we quantify the probability of a P2P user of being contacted by such entities. We observe that 100% of our nodes run into entities in these lists. In fact, 12 to 17% of all distinct IPs contacted by any node were listed on blocklists.
Anirban Banerjee, Michalis F aloutsos, and Laxmi Bhuyan
Department of Computer Science and Engineering
University of California, Riverside
Riverside, CA 92521.
Peer-to-peer networks, P2P, Gnutella, RIAA, User monitoring
Anirban Banerjee, Michalis F aloutsos, and Laxmi Bhuyan
Department of Computer Science and Engineering
University of California, Riverside
Riverside, CA 92521.
Peer-to-peer networks, P2P, Gnutella, RIAA, User monitoring
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