RERS BASED ON BEHAVIOR ANALYSIS

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.