A Fingerprint Template Protection Scheme Using Arnold Transform and Bio-hashing

Abstract

Fingerprint biometric is popularly used for protecting digital devices and applications. They are better and more reliable for authentication in comparison to the usual security tokens or password, which make them to be at the forefront of identity management systems. Though, they have several security benefits, there are several weaknesses of the fingerprint biometric recognition system. The greatest challenge of the fingerprint biometric system is theft or leakage of the template information. Also, each individual has limited and unique fingerprint which is permanent throughout their lifespan, hence, the compromise of the fingerprint biometric will cause a lifetime threat to the security and privacy of such an individual. Security and privacy risk of fingerprint biometric have previously been studied in the context of cryptosystem and cancelable biometric generation. However, these approaches do not obviously address the issue of revocability, diversity and irreversibility of fingerprint features to guard against the wrong use or theft of fingerprint biometric information. In this paper, we proposed a model that harnesses the strength of Arnold transform and Bio-hashing on fingerprint biometric features to overcome the limitations commonly encountered in sole fingerprint biometric approaches. In the experimental analysis, the result of irreversibility showed 0% False Acceptance Rate (FAR), performance showed maximum of 0.2% FAR and maximum of 0.8% False Rejection Rate (FRR) at different threshold values. Also, the result of renewability/revocability at SMDKAB SMKADKB and SMKBDKA showed that the protection did not match each other. Therefore, the performance of the proposed model was notable and the techniques could be efficiently and reliably used to enforce protection on biometric templates in establishments/organizations so that their information and processes could be secured.

A Survey of Biometric Authentication Technologies Towards Secure And Robust Systems: A Case Study of Mount Kenya University

“…Furthermore, every individual has a finite and unique fingerprint that remains constant throughout their lifetime; hence, a breach of the fingerprint biometric poses a lifetime danger to an individual's security and privacy. (Onifade, 2020).…”