UCL Discovery Stage
UCL home » Library Services » Electronic resources » UCL Discovery Stage

Quantifying Web Adblocker Privacy

Gervais, Arthur; Filios, Alexandros; Lenders, Vincent; Capkun, Srdjan; (2017) Quantifying Web Adblocker Privacy. In: Computer Security – ESORICS 2017. (pp. pp. 21-42). Springer: Cham, Switzerland. Green open access

[thumbnail of 2016-900.pdf]
Preview
Text
2016-900.pdf - Other

Download (416kB) | Preview

Abstract

Web advertisements, an integral part of today’s web browsing experience, financially support countless websites. Meaningful advertisements, however, require behavioral targeting, user tracking and profile fingerprinting that raise serious privacy concerns. To counter privacy issues and enhance usability, adblockers emerged as a popular way to filter web requests that do not serve the website’s main content. Despite their popularity, little work has focused on quantifying the privacy provisions of adblockers. In this paper, we develop a quantitative approach to objectively compare the privacy of adblockers. We propose a model based on a set of privacy metrics that captures not only the technical web architecture, but also the underlying corporate institutions of the problem across time and geography. We investigate experimentally the effect of various combinations of ad-blocking software and browser settings on 1000 Web sites. Our results highlight a significant difference among adblockers in terms of filtering performance, in particular affected by the applied configurations. Besides the ability to judge the filtering capabilities of existing adblockers and their particular configurations, our work provides a general framework to evaluate new adblocker proposals.

Type: Proceedings paper
Title: Quantifying Web Adblocker Privacy
Event: European Symposium on Research in Computer Security ESORICS 2017
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-66399-9_2
Publisher version: https://doi.org/10.1007/978-3-319-66399-9_2
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10182346
Downloads since deposit
1,540Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item