Disguised Chromium Browser: Robust Browser, Flash and Canvas Fingerprinting Protection

Peter Baumann; Stefan Katzenbeisser; Martin Stopczynski; Erik Tews

doi:10.1145/2994620.2994621

Disguised Chromium Browser: Robust Browser, Flash and Canvas Fingerprinting Protection

Peter Baumann, Stefan Katzenbeisser, Martin Stopczynski, Erik Tews

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Citations (Scopus)

Abstract

Browser fingerprinting is a widely used technique to uniquely identify web users and to track their online behavior. Until now, different tools have been proposed to protect the user against browser fingerprinting. However, these tools have usability restrictions as they deactivate browser features and plug-ins (like Flash) or the HTML5 canvas element. In addition, all of them only provide limited protection, as they randomize browser settings with unrealistic parameters or have methodical flaws, making them detectable for trackers.

In this work we demonstrate the first anti-fingerprinting strategy, which protects against Flash fingerprinting without deactivating it, provides robust and undetectable anti-canvas fingerprinting, and uses a large set of real word data to hide the actual system and browser properties without losing usability. We discuss the methods and weaknesses of existing anti-fingerprinting tools in detail and compare them to our enhanced strategies. Our evaluation against real world fingerprinting tools shows a successful fingerprinting protection in over 99% of 70.000 browser sessions.

Original language	English
Title of host publication	Proceedings of the 2016 ACM on Workshop on Privacy in the Electronic Society
Place of Publication	New York, NY, USA
Publisher	Association for Computing Machinery (ACM)
Pages	37-46
Number of pages	10
ISBN (Print)	978-1-4503-4569-9
DOIs	https://doi.org/10.1145/2994620.2994621
Publication status	Published - 2016

Publication series

Name	WPES '16
Publisher	ACM

Keywords

tracking
browser
canvas
fingerprinting
flash
privacy

Access to Document

10.1145/2994620.2994621Licence: None: All rights reserved

Cite this

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title = "Disguised Chromium Browser: Robust Browser, Flash and Canvas Fingerprinting Protection",

abstract = "Browser fingerprinting is a widely used technique to uniquely identify web users and to track their online behavior. Until now, different tools have been proposed to protect the user against browser fingerprinting. However, these tools have usability restrictions as they deactivate browser features and plug-ins (like Flash) or the HTML5 canvas element. In addition, all of them only provide limited protection, as they randomize browser settings with unrealistic parameters or have methodical flaws, making them detectable for trackers.In this work we demonstrate the first anti-fingerprinting strategy, which protects against Flash fingerprinting without deactivating it, provides robust and undetectable anti-canvas fingerprinting, and uses a large set of real word data to hide the actual system and browser properties without losing usability. We discuss the methods and weaknesses of existing anti-fingerprinting tools in detail and compare them to our enhanced strategies. Our evaluation against real world fingerprinting tools shows a successful fingerprinting protection in over 99% of 70.000 browser sessions.",

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series = "WPES '16",

publisher = "Association for Computing Machinery (ACM)",

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booktitle = "Proceedings of the 2016 ACM on Workshop on Privacy in the Electronic Society",

address = "United States",

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Disguised Chromium Browser: Robust Browser, Flash and Canvas Fingerprinting Protection. / Baumann, Peter; Katzenbeisser, Stefan; Stopczynski, Martin et al.
Proceedings of the 2016 ACM on Workshop on Privacy in the Electronic Society. New York, NY, USA: Association for Computing Machinery (ACM), 2016. p. 37-46 (WPES '16).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Browser fingerprinting is a widely used technique to uniquely identify web users and to track their online behavior. Until now, different tools have been proposed to protect the user against browser fingerprinting. However, these tools have usability restrictions as they deactivate browser features and plug-ins (like Flash) or the HTML5 canvas element. In addition, all of them only provide limited protection, as they randomize browser settings with unrealistic parameters or have methodical flaws, making them detectable for trackers.In this work we demonstrate the first anti-fingerprinting strategy, which protects against Flash fingerprinting without deactivating it, provides robust and undetectable anti-canvas fingerprinting, and uses a large set of real word data to hide the actual system and browser properties without losing usability. We discuss the methods and weaknesses of existing anti-fingerprinting tools in detail and compare them to our enhanced strategies. Our evaluation against real world fingerprinting tools shows a successful fingerprinting protection in over 99% of 70.000 browser sessions.

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