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.
Highlights
Since the advent of the Internet, various network technologies have been proposed, and the number of users has grown rapidly
We evaluate the performance of the extension recognition system, BEFP. e experimental environment is 4-core Intel Xeon E5-2682 V4 CPU, 8 GB memory, Windows 2016 x64 operating system, and the web browser is Google Chrome 83.0.4103.116
With the emergence of various defense measures, the extension fingerprinting technologies based on WAR and DOM cannot accurately identify the user-installed extension list
Summary
Since the advent of the Internet, various network technologies have been proposed, and the number of users has grown rapidly. For extensions that do not modify or update JavaScript properties, we design a behavioral fingerprinting technology that recognizes an extension based on its operation behavior (add, delete, modify) on the web page’s DOM. We comprehensively use the above two technologies to design an efficient browser extension recognition system, BEFP (Behavioral and Environmental Fingerprinting), in order to further improve the uniqueness of extension fingerprint. (i) We propose a new extension fingerprinting technology, JavaScript-based environmental fingerprinting, which relies on the difference in the effect of extensions on JavaScript properties and can break the existing extension fingerprint defense schemes. (ii) In addition, for extensions that do not modify or update JavaScript properties, behavioral fingerprinting is designed to fingerprint extensions using their behavior on the web page’s DOM It can resist the existing defense measures of DOM modification-based fingerprinting.
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