DRAWNAPART: A Device Identification and Spoofing Detection Technique Based on Remote GPU Fingerprinting

Browser fingerprinting aims to identify users or their devices, through scripts that execute in the users’ browser and collect information on software or hardware characteristics. It is used to track users or as an additional means of identification to improve security. Fingerprinting techniques have one significant limitation: they are unable to track individual users for an extended duration. This happens because browser fingerprints evolve over time, and these evolutions ultimately cause a fingerprint to be confused with those from other devices sharing similar hardware and software. Our technique, DrawnApart , advances the field of browser fingerprinting in three significant ways. First, it is the pioneering work that investigates and exploits manufacturing variances in identical GPUs in the context of privacy protection. Second, it provides a robust method for differentiating between devices with identical hardware and software configurations, achieving practical accuracy improvements in real-world scenarios. In a setting with diverse hardware and software configurations, DrawnApart is most effective when combined with traditional fingerprinting techniques such as FP-Stalker [74]. Third, DrawnApart introduces a capability to verify the GPU renderer string, enabling the detection of spoofing attempts aimed at bypassing two-factor authentication by mimicking the victim’s device attributes.

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Publication Details

Journal
ACM Transactions on Privacy and Security
Published
2026-07-22
DOI
https://doi.org/10.1145/3830402
Primary Topic
Internet Traffic Analysis and Secure E-voting
Type
article
Field-Weighted Citation Impact
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article

DRAWNAPART: A Device Identification and Spoofing Detection Technique Based on Remote GPU Fingerprinting

Yossi Oren, Naif Mehanna, Clémentine Maurice, Pierre Laperdrix et al.
ACM Transactions on Privacy and Security
Internet Traffic Analysis and Secure E-voting
article

DRAWNAPART: A Device Identification and Spoofing Detection Technique Based on Remote GPU Fingerprinting

Yossi Oren, Naif Mehanna, Clémentine Maurice, Pierre Laperdrix, Walter Rudametkin, Vitaly Dyadyuk, Yuval Yarom, Antonin Durey, Romain Rouvoy, Tomer Laor
article en

Abstract

Browser fingerprinting aims to identify users or their devices, through scripts that execute in the users’ browser and collect information on software or hardware characteristics. It is used to track users or as an additional means of identification to improve security. Fingerprinting techniques have one significant limitation: they are unable to track individual users for an extended duration. This happens because browser fingerprints evolve over time, and these evolutions ultimately cause a fingerprint to be confused with those from other devices sharing similar hardware and software. Our technique, DrawnApart , advances the field of browser fingerprinting in three significant ways. First, it is the pioneering work that investigates and exploits manufacturing variances in identical GPUs in the context of privacy protection. Second, it provides a robust method for differentiating between devices with identical hardware and software configurations, achieving practical accuracy improvements in real-world scenarios. In a setting with diverse hardware and software configurations, DrawnApart is most effective when combined with traditional fingerprinting techniques such as FP-Stalker [74]. Third, DrawnApart introduces a capability to verify the GPU renderer string, enabling the detection of spoofing attempts aimed at bypassing two-factor authentication by mimicking the victim’s device attributes.

ACM Transactions on Privacy and Security
Ben-Gurion University of the Negev (IL), Ruhr University Bochum (DE)
Peace, Justice and strong institutions
Openalex Percentile: Top 6%
Internet Traffic Analysis and Secure E-voting
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