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Missed by Filter Lists: Detecting Unknown Third-Party Trackers with Invisible Pixels

Imane Fouad 1 Nataliia Bielova 1 Arnaud Legout 2 Natasa Sarafijanovic-Djukic 2
1 PRIVATICS - Privacy Models, Architectures and Tools for the Information Society
CITI - CITI Centre of Innovation in Telecommunications and Integration of services, Inria Grenoble - Rhône-Alpes
2 DIANA - Design, Implementation and Analysis of Networking Architectures
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Web tracking has been extensively studied over the last decade. To detect tracking, previous studies and user tools rely on filter lists. However, it has been shown that filter lists miss trackers. In this paper, we propose an alternative method to detect trackers inspired by analyzing behavior of invisible pixels. By crawling 84,658 webpages from 8,744 domains, we detect that third-party invisible pixels are widely deployed: they are present on more than 94.51% of domains and constitute 35.66% of all third-party images. We propose a fine-grained behavioral classification of tracking based on the analysis of invisible pixels. We use this classification to detect new categories of tracking and uncover new collaborations between domains on the full dataset of 4,216,454 third-party requests. We demonstrate that two popular methods to detect tracking, based on EasyList & EasyPrivacy and on Disconnect lists respectively miss 25.22% and 30.34% of the trackers that we detect. Moreover, we find that if we combine all three lists, 379,245 requests originated from 8,744 domains still track users on 68.70% of websites.
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Submitted on : Tuesday, December 17, 2019 - 8:02:02 AM
Last modification on : Friday, December 10, 2021 - 1:16:03 PM
Long-term archiving on: : Wednesday, March 18, 2020 - 12:48:34 PM


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  • HAL Id : hal-01943496, version 4


Imane Fouad, Nataliia Bielova, Arnaud Legout, Natasa Sarafijanovic-Djukic. Missed by Filter Lists: Detecting Unknown Third-Party Trackers with Invisible Pixels. PETS 2020 - 20th Privacy Enhancing Technologies Symposium, Jul 2020, Montréal, Canada. ⟨hal-01943496v4⟩



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