Abstract
In this article, we introduce a new cancelable biometric template generation layout depending on selective encryption technology and Dual-Tree Complex Wavelet Transform (DT-CWT) fusion. The input face biometric is entered into the automatic face-segmentation (Viola-Jones) algorithm to detect the object in a short time. Viola-Jones algorithm can detect the left eye, right eye, nose, and mouth of the input biometric image. The encoder can choose the left or right eye to generate a cancelable biometric template. The selected eye image of size M × N is XORed with the created pseudo-random number (PRN) matrix CM × N to provide an initial primary image. Arnold Cat Map (ACM) is used to scramble the PRN matri pixel by pixel for primary image encryption keeping the pixel values themselves unchanged. Finally, the ACM scrambled eye images are encrypted using Advanced Encryption Standard (AES) algorithm for database storage. Moreover, the PRN and Initial Key (IK) of the AES algorithm for the same person are used for the biometric model authentication process for database storage. The IK is generated from the right finger and right eye fusion using DT-CWT technique. To avoid injury of a single eye, both right-eye and left-eye models are developed.
Highlights
Biometric identification methods based on human physiological characteristics such as face, iris, and fingerprints have become common practice
IASC, 2022, vol.33, no.2 protection of huge biometric database templates from unauthorized access can be achieved using selective encryption, chaos encryption, and strong encryption techniques like Advanced Encryption Standard (AES) [1–4]
We provide an introduction to cancelable biometrics concept, biometric system security and confidentiality issues, and the main contributions of the proposed cancelable biometric system
Summary
Biometric identification methods based on human physiological characteristics such as face, iris, and fingerprints have become common practice. A cancelable biometric system is required to manage biometric data through irreversible transformations to obtain biometric templates to maintain privacy. Multimodal biometric systems can reduce the Failure–To-Capture and Enroll (FTC/FTE) and provide greater resistance to plagiarism, since it is difficult to tamper with multiple biometric sources at the same time. Cancelable biometrics systems use irreversible transformations in one way to create transformed templates from the biometric data. Cancelable biometric systems provide resistance to template rebuilding, even if the spoofing process has access to both templates and transform parameters [5]. We provide an introduction to cancelable biometrics concept, biometric system security and confidentiality issues, and the main contributions of the proposed cancelable biometric system. We introduce the main contributions of the proposed cancelable biometric system.
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