Internet piracy has become a serious problem due to the expansion of network capacity and the availability of powerful hardware. To combat this problem, industry and law enforcement need a better understanding of the behavioral characteristics of Internet pirates. This paper describes a new conceptual framework for profiling Internet pirates. Also, it presents a taxonomy based on a survey of 114 Internet pirates. The taxonomy, which includes six types of downloaders and six types of file sharers with different behavioral characteristics, provides useful insights to forensic scientists and practitioners who are focused on combating Internet piracy.

Part 1: Internet Crime InvestigationsInternational audienceDetermining the source of criminal activity requires a reliable means to estimate a criminal’s identity. One way to do this is to use web browsing history to build a profile of an anonymous user. Since an individual’s web use is unique, matching the web use profile to known samples provides a means to identify an unknown user. This paper describes a model for web user profiling and identification. Two aspects of browsing behavior are examined to construct a user profile, the user’s page view number and page view time for each domain. Four weighting models, based on the term frequency and term frequency – inverse document frequency weighting schemes, are proposed and compared. Experiments involving 51 personal computers demonstrate that the profiling model is very effective at identifying web users

The expanding utilization of cyberlocker services is driven by the illegal exchange of copyrighted materials. In fact, the illegal exchange of copyrighted materials is the largest contributor to global Internet traffic. However, due to the anonymity provided by cyberlockers, it is difficult to track user identities directly from cyberlocker sites. Since cyberlocker users upload and share links via third-party sites, it is possible to harvest cyberlocker-related data from these sites and connect the data to specific users. This chapter describes a framework for collecting cyberlocker data from web forums and using cyberlocker link sharing behavior to identify users. Multidimensional scaling analysis and agglomerative hierarchical clustering analysis are performed on user profiles to yield clusters of forum users with similar sharing characteristics. The experimental results demonstrate that the framework provides valuable insights in investigations of cyberlocker-based piracy.

The growing popularity of cyberlocker service has led to significant impact on the Internet that it is considered as one of the biggest contributors to the global Internet traffic estimated to be illegally traded content. Due to the anonymity property of cyberlocker, it is difficult for investigators to track user identity directly on cyberlocker site. In order to find the potential relationships between cyberlocker users, we propose a framework to collect cyberlocker related data from public forums where cyberlocker users usually distribute cyberlocker links for others to download and identity information can be gathered easily. Different kinds of sharing behaviors of forum user are extracted to build the profile, which is then analyzed with statistical techniques. The experiment results demonstrate that the framework can effectively detect profiles with similar behaviors for identity tracking and produce a taxonomy of forum users to provide insights for investigating cyberlocker-based piracy.