Utilizing Web Trackers for Sybil Defense
ACM Transactions on the Web(2021)
摘要
AbstractUser 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.
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关键词
User tracking, recommendation engines, Sybil attacks
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