Section: New Results

Browser randomization against web tracking

Participants : Frédéric Besson, Thomas Jensen.

We have investigated different approaches for dynamically tracking information flows in order to improve web browser security. We have identified the problem of stateless web tracking (fingerprinting) and have proposed a novel approach to hybrid information flow monitoring by tracking the knowledge about secret variables using logical formulae. In a follow-up work we investigated how to enforce browser anonymity in the presence of finger-printing web trackers. One way to protect the users' privacy is to make them switch between different machine and browser configurations. We propose a formalisation of this privacy enforcement mechanism. We use information-theoretic channels to model the knowledge of the tracker and the fingerprinting program, and show how to synthesise a randomisation mechanism that defines the distribution of configurations for each user. This mechanism provides a strong guarantee of privacy (the probability of identifying the user is bounded by a given threshold) while maximising usability (the user switches to other configurations rarely). To find an optimal solution, we express the enforcement problem of randomisation by a linear program. We investigate and compare several approaches to randomisation and find that more efficient privacy enforcement would often provide lower usability. Finally, we relax the requirement of knowing the fingerprinting program in advance, by proposing a randomisation mechanism that guarantees privacy for an arbitrary program.