Open Access

ARTICLE

Selective Cancellable Multi-Biometric Template Generation Scheme Based on Multi-Exposure Feature Fusion

Ahmed M. Ayoup^1,*, Ashraf A. M. Khalaf¹, Fahad Alraddady², Fathi E. Abd El-Samie³, Walid El-Safai^3,5, Salwa M. Serag Eldin^2,4

1 Electrical Communications Engineering Department, Faculty of Engineering, Minia University, Minia, 61111, Egypt
2 Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif 21944, Saudi Arabia
3 Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menoufia, 32952, Egypt
4 Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt
5 Security Engineering Laboratory, Department of Computer Science, Prince Sultan University, Riyadh, 11586, Saudi Arabia

* Corresponding Author: Ahmed M. Ayoup. Email:

(This article belongs to this Special Issue: Soft Computing Methods for Intelligent Automation Systems)

Intelligent Automation & Soft Computing 2022, 33(1), 549-565. https://doi.org/10.32604/iasc.2022.024379

Received 15 October 2021; Accepted 16 November 2021; Issue published 05 January 2022

Abstract

This article introduces a new cancellable multi-biometric system based on the combination of a selective encryption method and a deep-learning-based fusion technology. The biometric face image is treated with an automatic face segmentation algorithm (Viola-Jones), and the image of the selected eye is XORed with a PRNG (Pseudo Random Number Generator) matrix. The output array is used to create a primary biometric template. This process changes the histogram of the selected eye image. Arnold’s Cat Map is used to superimpose the PRN pixels only on the pixels of the primary image. Arnold’s cat map deformed eyes are encrypted using the Advanced Encryption Standard (AES) to encrypt the biometric data stored in the database. In addition, the AES master key is used for the same person in the identity verification process to verify the biometric identity. It is created from the fingers of the right hand, and the right eye is integrated into this process using deep learning technology. The deep learning fusion process can prevent attacks on the biometric system as a whole. In order to avoid damage to the eye or fingerprint images, the design considers the other eye and fingerprint images.

---

Keywords

---