Measuring and Combatting Spam on Social Networks
Status: Ongoing
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.
Publications
- @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.
Project members
Collaboration with