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

AI-Assisted RF Fingerprinting for Identification of User Devices in...

Aishwarya Jawne (Center for Connected Autonomy & AI, Florida Atlantic University), Georgios Sklivanitis (Center for Connected Autonomy & AI, Florida Atlantic University), Dimitris A. Pados (Center for Connected Autonomy & AI, Florida Atlantic University), Elizabeth Serena Bentley (Air Force Research Laboratory)

Read More

Too Subtle to Notice: Investigating Executable Stack Issues in...

Hengkai Ye (The Pennsylvania State University), Hong Hu (The Pennsylvania State University)

Read More

Vision: Towards True User-Centric Design for Digital Identity Wallets

Yorick Last (Paderborn University), Patricia Arias Cabarcos (Paderborn University)

Read More

Cross-Origin Web Attacks via HTTP/2 Server Push and Signed...

Pinji Chen (Tsinghua University), Jianjun Chen (Tsinghua University & Zhongguancun Laboratory), Mingming Zhang (Zhongguancun Laboratory), Qi Wang (Tsinghua University), Yiming Zhang (Tsinghua University), Mingwei Xu (Tsinghua University), Haixin Duan (Tsinghua University)

Read More