Eluding ML-based Adblockers With Actionable Adversarial Examples

Zhu, Shitong; Wang, Zhongjie; Chen, Xun; Li, Shasha; Man, Keyu; Iqbal, Umar; Qian, Zhiyun; Chan, Kevin; Krishnamurthy, Srikanth V.; Shafiq, Zubair; Yu, Hao; Li, Guoren; Zhang, Zheng; Zou, Xiaochen

doi:10.1145/3485832.3488008

Cited by 3 publications

(1 citation statement)

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“…However, the latest functionalities added to web technologies in the form of new JavaScript APIs [30] permit stateless web tracking algorithms to collect much more precise information. Rendering differences due to specific hardware and software combinations can be abused by means of those APIs to precisely identify the browser being used to explore the web [31]- [35]. This kind of web tracking is far more intrusive than the traditional cookies, as it is completely transparent to the user, and there is no easy way to control when, where, or by whom they are being used.…”

Section: A Web Trackingmentioning

confidence: 99%

ASTrack: Automatic Detection and Removal of Web Tracking Code with Minimal Functionality Loss

Castell-Uroz,

Fukuda,

Barlet-Ros

2023

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications

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Recent advances in web technologies make it more difficult than ever to detect and block web tracking systems. In this work, we propose ASTrack, a novel approach to web tracking detection and removal. ASTrack uses an abstraction of the code structure based on Abstract Syntax Trees to selectively identify web tracking functionality shared across multiple web services. This new methodology allows us to: (i) effectively detect web tracking code even when using evasion techniques (e.g., obfuscation, minification, or webpackaging); and (ii) safely remove those portions of code related to tracking purposes without affecting the legitimate functionality of the website. Our evaluation with the top 10k most popular Internet domains shows that ASTrack can detect web tracking with high precision (98%), while discovering about 50k tracking code pieces and more than 3,400 new tracking URLs not previously recognized by most popular privacy-preserving tools (e.g., uBlock Origin). Moreover, ASTrack achieved a 36% reduction in functionality loss in comparison with the filter lists, one of the safest options available. Using a novel methodology that combines computer vision and manual inspection, we estimate that full functionality is preserved in more than 97% of the websites.

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Section: A Web Trackingmentioning

confidence: 99%