Measuring and Combatting Spam on Social Networks
As spam becomes prevalent on social networks, we study the techniques and characteristics of spam to build better defenses. In our initial study, we found that existing defenses designed to prevent email spam have little success at preventing social network spam, making a detailed study of spam characteristics a necessity. This project encompasses both the measurement and understanding of spam as well as the development of defenses suitable for deployment at large scale by social networks.
- @spam: The Underground on 140 Characters or Less. Chris Grier, Kurt Thomas, Vern Paxson, and Michael Zhang. Proceedings of the ACM Conference on Computer and Communications Security, October 2010. [pdf]
- Detecting and Analyzing Automated Activity on Twitter. C. M. Zhang and V. Paxson. Proceedings of Passive and Active Measurement, March 2011. [pdf]
- Design and Evaluation of a Real-Time URL Spam Filtering Service. Kurt Thomas, Chris Grier, Justin Ma, Vern Paxson, Dawn Song. Proceedings of the IEEE Symposium on Security and Privacy, May 2011. [pdf]
- Suspended Accounts in Retrospect: An Analysis of Twitter Spam. Kurt Thomas, Chris Grier, Vern Paxson, and Dawn Song. Proceedings of the Internet Measurement Conference, November 2011.
- Adapting Social Spam Infrastructure for Political Censorship. Kurt Thomas, Chris Grier, and Vern Paxson. Proceedings of the USENIX Workshop on Large-Scale Exploits and Emergent Threats (LEET). April 2012.
- Justin Ma (AMP Lab @ UC Berkeley)