Is it Possible to Generate Irreversible PolyProtected Templates from Face Embeddings using System-Specific Keys?
cs.CR, cs.CV
Submitted: 2026-10-01
Updated: 2026-10-01
Comments: Submitted to TIFS journal on 12 May 2026 (under review). Consists of: 13 pages, 9 figures, 3 tables
Code: https://github.com/deepinsight/insightface
License: http://creativecommons.org/licenses/by/4.0/
The gist: This work aims to answer the question of whether it is possible to generate irreversible protected templates when the PolyProtect biometric template protection method is applied to face embeddings
Terminology
Abstract
This work aims to answer the question of whether it is possible to generate irreversible protected templates when the PolyProtect biometric template protection method is applied to face embeddings using system-specific keys (i.e., the same C and E parameters, which define the transform, are applied to all subjects' face embeddings), instead of the traditional subject-specific keys (i.e., each subject has their own C and E parameters). This is important for determining whether we can perform de-duplication of face identities in the PolyProtected domain, which is not possible in the subject-specific key scenario due to the clash with PolyProtect's unlinkability property (i.e., one could generate multiple protected templates belonging to the same identity, using different C and E parameters, such that those templates cannot be linked to each other). We present experiments (reproducible using our open-source code) to prove that there exist at least three ways of systematically selecting system-specific keys that produce irreversible PolyProtected templates: (i) from pre-selected subject-specific keys, (ii) by applying a previously proposed key selection algorithm to random vectors, and (iii) by approximating a "good" C/E pair distribution from which system-specific keys can be constructed. Our findings thus point to the conclusion that it is, indeed, possible to safely operate PolyProtect in the system-specific key scenario without degrading the template protection potential. This opens up the possibility for identity de-duplication in the PolyProtected domain.
Sources
- Inverting face embeddings with convolutional neural networks
- Beyond Identity: What Information Is Stored in Biometric Face Templates?
- A Deeper Dive into the Irreversibility of PolyProtect: Making Protected Face Templates Harder to Invert
- in-Car Biometrics (iCarB) Datasets for Driver Recognition: Face, Fingerprint, and Voice
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