PriVaricator: Deceiving Fingerprinters with Little White Lies

Researchers have shown that, in recent years, unwanted web tracking is on the rise, with browser-based fingerprinting be-ing adopted by more and more websites as a viable alterna-tive 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 random-ization policies. We evaluate our techniques in terms of be-ing able to prevent fingerprinting and not breaking existing (benign) sites. The best of our randomization policies ren-ders 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