Meenatchi Sundaram Muthu Selva Annamalai (University College London), Igor Bilogrevic (Google), Emiliano De Cristofaro (University of California, Riverside)

Browser fingerprinting often provides an attractive alternative to third-party cookies for tracking users across the web. In fact, the increasing restrictions on third-party cookies placed by common web browsers and recent regulations like the GDPR may accelerate the transition. To counter browser fingerprinting, previous work proposed a number of techniques to detect its prevalence and severity. However, most – if not all – of those techniques rely on 1) centralized web crawls and/or 2) computationally-intensive operations to extract and process signals (e.g., information-flow and static analysis).

To address these limitations, we present FP-Fed, the first distributed system for browser fingerprinting detection. Using FP-Fed, users collaboratively train on-device models based on their real browsing patterns, without sharing their training data with a central entity, by relying on Differentially Private Federated Learning (DP-FL). To demonstrate its feasibility and effectiveness, we evaluate FP-Fed’s performance on a set of 20k popular websites with different privacy levels, numbers of participants, and features extracted from the scripts. Our experiments show that FP-Fed achieves reasonably high detection performance and can perform both training and inference efficiently, on-device, by only relying on runtime signals extracted from the execution trace, without requiring any resource-intensive operation.

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Clement Fung (Carnegie Mellon University), Eric Zeng (Carnegie Mellon University), Lujo Bauer (Carnegie Mellon University)

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Liheng Chen (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences; Institute for Network Science and Cyberspace of Tsinghua University), Zheming Li (Institute for Network Science and Cyberspace of Tsinghua University), Zheyu Ma (Institute for Network Science and Cyberspace of Tsinghua University), Yuan Li (Tsinghua University),…

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Michael Clark (Brigham Young University), Scott Ruoti (The University of Tennessee), Michael Mendoza (Imperial College London), Kent Seamons (Brigham Young University)

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