Utilizing web trackers for sybil defense

Marcel Flores, Andrew Kahn, Marc Warrior, Alan Mislove, Aleksandar Kuzmanovic

Research output: Contribution to journalArticlepeer-review


User tracking has become ubiquitous practice on the Web, allowing services to recommend behaviorally targeted content to users. In this article, we design Alibi, a system that utilizes such readily available personalized content, generated by recommendation engines in real time, as a means to tame Sybil attacks. In particular, by using ads and other tracker-generated recommendations as implicit user “certificates,” Alibi is capable of creating meta-profiles that allow for rapid and inexpensive validation of users’ uniqueness, thereby enabling an Internet-wide Sybil defense service. We demonstrate the feasibility of such a system, exploring the aggregate behavior of recommendation engines on the Web and demonstrating the richness of the meta-profile space defined by such inputs. We further explore the fundamental properties of such meta-profiles, i.e., their construction, uniqueness, persistence, and resilience to attacks. By conducting a user study, we show that the user meta-profiles are robust and show important scaling effects. We demonstrate that utilizing even a moderate number of popular Web sites empowers Alibi to tame large-scale Sybil attacks.

Original languageEnglish (US)
Article number8
JournalACM Transactions on the Web
Issue number2
StatePublished - May 2021


  • Recommendation engines
  • Sybil attacks
  • User tracking

ASJC Scopus subject areas

  • Computer Networks and Communications


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