TY - GEN
T1 - FPDetective
T2 - 2013 ACM SIGSAC Conference on Computer and Communications Security, CCS 2013
AU - Acar, Gunes
AU - Juarez, Marc
AU - Nikiforakis, Nick
AU - Diaz, Claudia
AU - Gürses, Seda
AU - Piessens, Frank
AU - Preneel, Bart
PY - 2013
Y1 - 2013
N2 - In the modern web, the browser has emerged as the vehicle of choice, which users are to trust, customize, and use, to access a wealth of information and online services. However, recent studies show that the browser can also be used to invisibly fingerprint the user: a practice that may have serious privacy and security implications. In this paper, we report on the design, implementation and deployment of FPDetective, a framework for the detection and analysis of web-based fingerprinters. Instead of relying on information about known fingerprinters or third-party-tracking blacklists, FPDetective focuses on the detection of the fingerprinting itself. By applying our framework with a focus on font detection practices, we were able to conduct a large scale analysis of the million most popular websites of the Internet, and discovered that the adoption of fingerprinting is much higher than previous studies had estimated. Moreover, we analyze two countermeasures that have been proposed to defend against fingerprinting and find weaknesses in them that might be exploited to bypass their protection. Finally, based on our findings, we discuss the current understanding of fingerprinting and how it is related to Personally Identifiable Information, showing that there needs to be a change in the way users, companies and legislators engage with fingerprinting.
AB - In the modern web, the browser has emerged as the vehicle of choice, which users are to trust, customize, and use, to access a wealth of information and online services. However, recent studies show that the browser can also be used to invisibly fingerprint the user: a practice that may have serious privacy and security implications. In this paper, we report on the design, implementation and deployment of FPDetective, a framework for the detection and analysis of web-based fingerprinters. Instead of relying on information about known fingerprinters or third-party-tracking blacklists, FPDetective focuses on the detection of the fingerprinting itself. By applying our framework with a focus on font detection practices, we were able to conduct a large scale analysis of the million most popular websites of the Internet, and discovered that the adoption of fingerprinting is much higher than previous studies had estimated. Moreover, we analyze two countermeasures that have been proposed to defend against fingerprinting and find weaknesses in them that might be exploited to bypass their protection. Finally, based on our findings, we discuss the current understanding of fingerprinting and how it is related to Personally Identifiable Information, showing that there needs to be a change in the way users, companies and legislators engage with fingerprinting.
KW - device fingerprinting
KW - dynamic analysis
KW - flash
KW - javascript
KW - privacy
KW - tracking
KW - web security
UR - https://www.scopus.com/pages/publications/84889043880
U2 - 10.1145/2508859.2516674
DO - 10.1145/2508859.2516674
M3 - Conference contribution
AN - SCOPUS:84889043880
SN - 9781450324779
T3 - Proceedings of the ACM Conference on Computer and Communications Security
SP - 1129
EP - 1140
BT - CCS 2013 - Proceedings of the 2013 ACM SIGSAC Conference on Computer and Communications Security
Y2 - 4 November 2013 through 8 November 2013
ER -