Maxime Huyghe (Univ. Lille, Inria, CNRS, UMR 9189 CRIStAL), Clément Quinton (Univ. Lille, Inria, CNRS, UMR 9189 CRIStAL), Walter Rudametkin (Univ. Rennes, Inria, CNRS, UMR 6074 IRISA)

Web browsers have become complex tools used by billions of people. The complexity is in large part due to its adaptability and variability as a deployment platform for modern applications, with features continuously being added. This also has the side effect of exposing configuration and hardware properties that are exploited by browser fingerprinting techniques.

In this paper, we generate a large dataset of browser fingerprints using multiple browser versions, system and hardware configurations, and describe a tool that allows reasoning over the links between configuration parameters and browser fingerprints. We argue that using generated datasets that exhaustively explore configurations provides developers, and attackers, with important information related to the links between configuration parameters (i.e., browser, system and hardware configurations) and their exhibited browser fingerprints. We also exploit Browser Object Model (BOM) enumeration to obtain exhaustive browser fingerprints composed of up to 16, 000 attributes.

We propose to represent browser fingerprints and their configurations with feature models, a tree-based representation commonly used in Software Product Line Engineering (SPLE) to respond to the challenges of variability, to provide a better abstraction to represent browser fingerprints and configurations. With translate 89, 486 browser fingerprints into a feature model with 35, 857 nodes from 1, 748 configurations. We show the advantages of this approach, a more elegant tree-based solution, and propose an API to query the dataset. With these tools and our exhaustive configuration exploration, we provide multiple use cases, including differences between headless and headful browsers or the selection of a minimal set of attributes from browser fingerprints to re-identify a configuration parameter from the browser.

View More Papers

Work-in-Progress: Manifest V3 Unveiled: Navigating the New Era of...

Nikolaos Pantelaios and Alexandros Kapravelos (North Carolina State University)

Read More

EAGLEYE: Exposing Hidden Web Interfaces in IoT Devices via...

Hangtian Liu (Information Engineering University), Lei Zheng (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University), Shuitao Gan (Laboratory for Advanced Computing and Intelligence Engineering), Chao Zhang (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University), Zicong Gao (Information Engineering University), Hongqi Zhang (Henan Key Laboratory of Information Security), Yishun Zeng (Institute for Network Sciences…

Read More

URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learning

Duanyi Yao (Hong Kong University of Science and Technology), Songze Li (Southeast University), Xueluan Gong (Wuhan University), Sizai Hou (Hong Kong University of Science and Technology), Gaoning Pan (Hangzhou Dianzi University)

Read More

Translating C To Rust: Lessons from a User Study

Ruishi Li (National University of Singapore), Bo Wang (National University of Singapore), Tianyu Li (National University of Singapore), Prateek Saxena (National University of Singapore), Ashish Kundu (Cisco Research)

Read More