# A Cryptanalysis of Two Cancelable Biometric Schemes based on Index-of-Max Hashing

arXiv: https://arxiv.org/abs/1910.01389 · HTML: https://mlsanity.com/paper/1910.01389/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Oct 2019.

## Built on by (most cited first, 9 of 9)

- [Deep Face Fuzzy Vault: Implementation and Performance](https://mlsanity.com/paper/2102.02458/) (2021)
- [Feature Fusion Methods for Indexing and Retrieval of Biometric Data: Application to Face Recognition with Privacy Protection](https://mlsanity.com/paper/2107.12675/) (2021)
- [IDFace: Face Template Protection for Efficient and Secure Identification](https://mlsanity.com/paper/2507.12050/) (2025)
- [Blind-Match: Efficient Homomorphic Encryption-Based 1:N Matching for Privacy-Preserving Biometric Identification](https://mlsanity.com/paper/2408.06167/) (2024)
- [Random Hash Code Generation for Cancelable Fingerprint Templates using Vector Permutation and Shift-order Process](https://mlsanity.com/paper/2105.10227/) (2021)
- [Authentication Attacks on Projection-based Cancelable Biometric Schemes](https://mlsanity.com/paper/2110.15163/) (2021)
- [Optimizing Key-Selection for Face-based One-Time Biometrics via Morphing](https://mlsanity.com/paper/2310.02997/) (2023)
- [Cryptanalysis of Cancelable Biometrics Vault](https://mlsanity.com/paper/2501.05786/) (2025)
- [Model Inversion meets Cryptographic Fuzzy Extractors](https://mlsanity.com/paper/2510.25687/) (2025)

## Abstract (arXiv)

Cancelable biometric schemes generate secure biometric templates by combining user specific tokens and biometric data. The main objective is to create irreversible, unlinkable, and revocable templates, with high accuracy in matching. In this paper, we cryptanalyze two recent cancelable biometric schemes based on a particular locality sensitive hashing function, index-of-max (IoM): Gaussian Random Projection-IoM (GRP-IoM) and Uniformly Random Permutation-IoM (URP-IoM). As originally proposed, these schemes were claimed to be resistant against reversibility, authentication, and linkability attacks under the stolen token scenario. We propose several attacks against GRP-IoM and URP-IoM, and argue that both schemes are severely vulnerable against authentication and linkability attacks. We also propose better, but not yet practical, reversibility attacks against GRP-IoM. The correctness and practical impact of our attacks are verified over the same dataset provided by the authors of these two schemes.