Abstract: Early detection of high volume swarms in a peer-to-peer network, including a data feed of peer-to-peer swarm activity, and an analytics engine processing the data feed and identifying the high volume swarms that have parameters that exceed a threshold. The system can include a pre-processing section for conditioning the swarm data for the analytics section. There can also be a verification section that confirms that the peer download file matches the target file. The early detection provides for enhanced anti-piracy efforts, improved allocation of network resources, and better business decision-making.

Abstract: Early detection of high volume swarms in a peer-to-peer network, including a data feed of peer-to-peer swarm activity, and an analytics engine processing the data feed and identifying the high volume swarms that have parameters that exceed a threshold. The system can include a pre-processing section for conditioning the swarm data for the analytics section. There can also be a verification section that confirms that the peer download file matches the target file. The early detection provides for enhanced anti-piracy efforts, improved allocation of network resources, and better business decision-making.

Abstract: Tracking digital asset infringement activities and infringers on peer-to-peer networks. One method for assessing notice effectiveness of unauthorized distributors of content on a peer-to-peer network comprises processing peer data from a plurality of peers on the network, wherein the peer data aids in identification of individual unauthorized distributors. The embodiment includes creating a trial with a trial base population of the unauthorized distributors and a trial capture window, determining metrics for measuring the notice effectiveness, selecting a randomization methodology for the trial, performing the trial with the trial base population over the trial capture window according to the randomization methodology and issuing notices to some of the unauthorized distributors.