# Random Hash Code Generation for Cancelable Fingerprint Templates using Vector Permutation and Shift-order Process

arXiv: https://arxiv.org/abs/2105.10227 · HTML: https://mlsanity.com/paper/2105.10227/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 37 references that are in the map.
- First posted on arXiv 21 May 2021.

## Builds on (most cited first, 3 of 3)

- [Ranking Based Locality Sensitive Hashing Enabled Cancelable Biometrics: Index-of-Max Hashing](https://mlsanity.com/paper/1703.05455/) (2017)
- [A Cryptanalysis of Two Cancelable Biometric Schemes based on Index-of-Max Hashing](https://mlsanity.com/paper/1910.01389/) (2019)
- [Interpretable security analysis of cancellable biometrics using constrained-optimized similarity-based attack](https://mlsanity.com/paper/2006.13051/) (2020)

## Abstract (arXiv)

Cancelable biometric techniques have been used to prevent the compromise of biometric data by generating and using their corresponding cancelable templates for user authentication. However, the non-invertible distance preserving transformation methods employed in various schemes are often vulnerable to information leakage since matching is performed in the transformed domain. In this paper, we propose a non-invertible distance preserving scheme based on vector permutation and shift-order process. First, the dimension of feature vectors is reduced using kernelized principle component analysis (KPCA) prior to randomly permuting the extracted vector features. A shift-order process is then applied to the generated features in order to achieve non-invertibility and combat similarity-based attacks. The generated hash codes are resilient to different security and privacy attacks whilst fulfilling the major revocability and unlinkability requirements. Experimental evaluation conducted on 6 datasets of FVC2002 and FVC2004 reveals a high-performance accuracy of the proposed scheme better than other existing state-of-the-art schemes.