TY - GEN
T1 - PriVaricator
T2 - 24th International Conference on World Wide Web, WWW 2015
AU - Nikiforakis, Nick
AU - Joosen, Wouter
AU - Livshits, Benjamin
PY - 2015/5/18
Y1 - 2015/5/18
N2 - Researchers have shown that, in recent years, unwanted web tracking is on the rise, with browser-based fingerprinting being adopted by more and more websites as a viable alternative to third-party cookies. In this paper we propose PriVaricator, a solution to the problem of browser-based fingerprinting. A key insight is that when it comes to web tracking, the real problem with fingerprinting is not uniqueness of a fingerprint, it is linka-bility, i.e., the ability to connect the same fingerprint across multiple visits. Thus, making fingerprints non-deterministic also makes them hard to link across browsing sessions. In PriVaricator we use the power of randomization to \break" linkability by exploring a space of parameterized randomization policies. We evaluate our techniques in terms of being able to prevent fingerprinting and not breaking existing (benign) sites. The best of our randomization policies renders all the fingerprinters we tested ineffective, while causing minimal damage on a set of 1,000 Alexa sites on which we tested, with no noticeable performance overhead.
AB - Researchers have shown that, in recent years, unwanted web tracking is on the rise, with browser-based fingerprinting being adopted by more and more websites as a viable alternative to third-party cookies. In this paper we propose PriVaricator, a solution to the problem of browser-based fingerprinting. A key insight is that when it comes to web tracking, the real problem with fingerprinting is not uniqueness of a fingerprint, it is linka-bility, i.e., the ability to connect the same fingerprint across multiple visits. Thus, making fingerprints non-deterministic also makes them hard to link across browsing sessions. In PriVaricator we use the power of randomization to \break" linkability by exploring a space of parameterized randomization policies. We evaluate our techniques in terms of being able to prevent fingerprinting and not breaking existing (benign) sites. The best of our randomization policies renders all the fingerprinters we tested ineffective, while causing minimal damage on a set of 1,000 Alexa sites on which we tested, with no noticeable performance overhead.
KW - Fingerprinting
KW - Randomization
KW - Tracking
UR - https://www.scopus.com/pages/publications/84968765165
U2 - 10.1145/2736277.2741090
DO - 10.1145/2736277.2741090
M3 - Conference contribution
AN - SCOPUS:84968765165
T3 - WWW 2015 - Proceedings of the 24th International Conference on World Wide Web
SP - 820
EP - 830
BT - WWW 2015 - Proceedings of the 24th International Conference on World Wide Web
PB - Association for Computing Machinery, Inc
Y2 - 18 May 2015 through 22 May 2015
ER -