Evaluating anti-fingerprinting privacy enhancing technologies

Abstract

We study how to evaluate Anti-Fingerprinting Privacy Enhancing Technologies (AFPETs). Experimental methods have the advantage of control and precision, and can be applied to new AFPETs that currently lack a user base. Observational methods have the advantage of scale and drawing from the browsers currently in real-world use. We propose a novel combination of these methods, offering the best of both worlds, by applying experimentally created models of a AFPET's behavior to an observational dataset. We apply our evaluation methods to a collection of AFPETs to find the Tor Browser Bundle to be the most effective among them. We further uncover inconsistencies in some AFPETs' behaviors.