BEFP: An Extension Recognition System Based on Behavioral and Environmental Fingerprinting

Abstract

Browser extensions are third-party applications that can customize the browsing experience. Previous studies have shown that browser extension fingerprinting can be used to track users and reveal users’ privacy information by obtaining the browser extension list. However, the proposal of various defense measures weakens the effectiveness of the existing extension fingerprinting technologies. In this paper, we first propose two extension fingerprinting technologies: JavaScript-based environmental fingerprinting and DOM-based behavioral fingerprinting. They, respectively, capture the operation behaviors of extensions on JavaScript properties and webpage’s DOM. Second, we design BEFP, an extension recognition system which comprehensively utilizes the above two technologies to improve the uniqueness of the extension fingerprint. Finally, we collect the latest data set and carry out experiments on the actual scenario where users install multiple extensions. The results show that the true positive rate of extension recognition is as high as 96.3%. And the extension’s detectable rate of BEFP is superior to the existing technologies. Moreover, it is proved that the JavaScript-based environmental fingerprinting can complement the DOM-based fingerprinting to distinguish the extensions with the same DOM modification.