Online Social Network Security


Online social networks (OSNs) are extremely popular among Internet users. However, spam originating from friends and acquaintances in OSNs not only reduces the joy of Internet surfing, but also may cause damage to less security-savvy users. While spam filtering techniques have been significantly advanced, spammers constantly adapt their spamming strategy to avoid detection.

In this project, we develop Tangram, a framework that incorporates multiple heterogeneous techniques to mitigate OSN spam and to protect OSN users. The heterogeneous detection techniques attack spam from different angles and complement each other. The system is designed to integrate into the OSN platform. It inspects the user generated message stream and block spam message directly. The process is transparent to OSN users. Tangram contains three major detection modules: 1) online campaign discovery module, 2) spam template generation module, and 3) malicious domain group detection module. The online campaign discovery module and the spam template generation module detect OSN spam online, whereas the malicious domain group detection module works offline. Although the offline module does not directly detects OSN spam, it supplies training samples to the online modules.





System Release

We make available a list of tools and datasets that we developed in this project.