The socialbot attack model is a spiritual successor to the Sybil attack model that addresses several of its flaws. Where the Sybil model makes strong assumptions about the number and organization of the attackers, the socialbot model relaxes those. A socialbot is simply a bot that pretends to be a human on a social network. Therefore, a socialbot attack could consist of only a single attacker or an army of loosely-coordinated assailants.

Objectives:

• Devise theoretically optimal socialbot attacks, and study their limitations and how to exploit them for defense.
• Examine the impact of user behaviors on socialbot attacks, and study how attackers may exploit or suffer from these behaviors.

Selected Publications:

• Xiang Li, J David Smith, and My T. Thai. “Adaptive Crawling with Multiple Bots: A Matroid Intersection Approach,” in Proceedings of INFOCOM, 2018
• J David Smith, Alan Kuhnle, and My T. Thai. “An Approximately Optimal Bot for Non-Submodular Social Reconnaissance,” in Proceedings of HyperText, 2018
• Xiang Li, J David Smith, and My T. Thai. “Adaptive Reconnaissance Attacks with Near-Optimal Parallel Batching,” in Proceedings of ICDCS, 2017