Hypersphere Secure Sketch Revisited: Probabilistic Linear Regression Attack on IronMask in Multiple Usage

Protection of biometric templates is a critical and urgent area of focus. IronMask demonstrates superior recognition performance while protecting facial templates against existing known attacks. In high-level, IronMask can be conceptualized as a fuzzy commitment scheme building on the hypersphere directly. We devise an attack on IronMask targeting on the security notion of renewability. Our attack, termed as Probabilistic Linear Regression Attack, utilizes the linearity of underlying used error correcting code. This attack is the first algorithm to successfully recover the original template when getting multiple protected templates in acceptable time and requirement of storage. We implement experiments on IronMask applied to protect ArcFace that well verify the validity of our attacks. Furthermore, we carry out experiments in noisy environments and confirm that our attacks are still applicable. Finally, we discuss two strategies to mitigate this type of attacks.

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Publication Details

Journal
Proceedings on Privacy Enhancing Technologies
Published
2025-07-13
DOI
https://doi.org/10.56553/popets-2025-0154
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
0.00
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article

Hypersphere Secure Sketch Revisited: Probabilistic Linear Regression Attack on IronMask in Multiple Usage

Pengxu Zhu, Lei Wang
Proceedings on Privacy Enhancing Technologies
Generative Adversarial Networks and Image Synthesis
article

Hypersphere Secure Sketch Revisited: Probabilistic Linear Regression Attack on IronMask in Multiple Usage

Pengxu Zhu, Lei Wang
article en

Abstract

Protection of biometric templates is a critical and urgent area of focus. IronMask demonstrates superior recognition performance while protecting facial templates against existing known attacks. In high-level, IronMask can be conceptualized as a fuzzy commitment scheme building on the hypersphere directly. We devise an attack on IronMask targeting on the security notion of renewability. Our attack, termed as Probabilistic Linear Regression Attack, utilizes the linearity of underlying used error correcting code. This attack is the first algorithm to successfully recover the original template when getting multiple protected templates in acceptable time and requirement of storage. We implement experiments on IronMask applied to protect ArcFace that well verify the validity of our attacks. Furthermore, we carry out experiments in noisy environments and confirm that our attacks are still applicable. Finally, we discuss two strategies to mitigate this type of attacks.

Proceedings on Privacy Enhancing TechnologiesVol. 2025(4)
Shanghai Jiao Tong University (CN)
Openalex Percentile: Top 85%
Generative Adversarial Networks and Image Synthesis
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