Article: A novel Boolean approach for cancellable biometric template generation Journal: International Journal of Biometrics (IJBM) 2025 Vol.17 No.6 pp.544 - 569 Abstract: Cancellable biometrics addresses privacy and security concerns by transforming biometric data into a non-invertible template. This paper presents two novel and secure binary domain transformations for generating cancellable templates from biometric images. Our approach involves converting pixel decimal values to their unsigned binary equivalents, significantly enhancing non-invertibility. Experimental results on eight datasets demonstrate superior performance, achieving an equal error rate (EER) below 0.001%, outperforming five leading cancellable biometric methods based on salting, XOR, and random permutations. Inverse attack, attack via record multiplicity (ARM), and similarity metrics confirm the non-invertibility and robustness of the generated templates. False accept and brute force attack analysis prove that the methods are secure. Both methods adhere to the essential requirements of cancellable biometrics, allowing the cancellation of templates and demonstrating improved recognition accuracy. This makes both of them feasible for secure biometric authentication. Inderscience Publishers - linking academia, business and industry through research

Title: A novel Boolean approach for cancellable biometric template generation

Authors: Onkar Singh; Ajay Jaiswal; Nitin Kumar; Naveen Kumar

Addresses: Department of Computer Science, Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India ' Department of Distance and Continuing Education, Campus of Open Learning, University of Delhi, Delhi, India ' Department of Computer Science and Engineering, Punjab Engineering College, Chandigarh, India ' Department of Computer Science, Faculty of Mathematical Sciences, University of Delhi, Delhi, India

Abstract: Cancellable biometrics addresses privacy and security concerns by transforming biometric data into a non-invertible template. This paper presents two novel and secure binary domain transformations for generating cancellable templates from biometric images. Our approach involves converting pixel decimal values to their unsigned binary equivalents, significantly enhancing non-invertibility. Experimental results on eight datasets demonstrate superior performance, achieving an equal error rate (EER) below 0.001%, outperforming five leading cancellable biometric methods based on salting, XOR, and random permutations. Inverse attack, attack via record multiplicity (ARM), and similarity metrics confirm the non-invertibility and robustness of the generated templates. False accept and brute force attack analysis prove that the methods are secure. Both methods adhere to the essential requirements of cancellable biometrics, allowing the cancellation of templates and demonstrating improved recognition accuracy. This makes both of them feasible for secure biometric authentication.

Keywords: Boolean-XOR; biometric salting; biometric recognition; template protection; privacy; security.

DOI: 10.1504/IJBM.2025.149667

International Journal of Biometrics, 2025 Vol.17 No.6, pp.544 - 569

Received: 24 Dec 2024
Accepted: 19 May 2025
Published online: 10 Nov 2025 *

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Title: A novel Boolean approach for cancellable biometric template generation

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