Received May 20, 2020, accepted May 28, 2020, date of publication June 3, 2020, date of current version June 16, 2020. Digital Object Identifier 10.1109/ACCESS.2020.2999656 A Novel Cancelable FaceHashing Technique Based on Non-Invertible Transformation With Encryption and Decryption Template ALAMGIR SARDAR 1 , SAIYED UMER 1 , CHIARA PERO 2 , AND MICHELE NAPPI 2 , (Senior Member, IEEE) 1 Department of Computer Science and Engineering, Aliah University, Kolkata 700156, India 2 Department of Computer Science, University of Salerno, 84084 Fisciano, Italy Corresponding author: Chiara Pero (cpero@unisa.it) This work was supported in part by the Italian National Research Project PRIN 2015 (201548C5NT) entitled ‘‘COntactlesS Multibiometric mObile System in the wild: COSMOS.’’ ABSTRACT A novel cancelable FaceHashing technique based on non-invertible transformation with encryption and decryption template has been proposed in this paper. The proposed system has four com- ponents: face preprocessing, feature extraction, cancelable feature extraction followed by the classification, and encryption/decryption of cancelable face feature templates. During face preprocessing, the facial region of interest has been extracted out to speed the process for evaluating discriminant features. In feature extraction, some optimization techniques such as Sparse Representation Coding, Coordinate descent, and Block coordinates descent have been employed on facial descriptors to obtain the best representative of those descriptors. The representative descriptors are further arranged in a spatial pyramid matching structure to extract more discriminant and distinctive feature vectors. To preserve them, the existing BioHashing technique has been modified and extended to some higher levels of security attacks and the modified BioHashing technique computes a cancelable feature vector by the combined effect of the facial feature vector and the assigned token correspond to each user. The elements of computed cancelable feature vector are in a numeric form that has been employed to perform both verifications as well as identification task in online while the original facial feature vectors are kept offline either in hard drive or disc. Then, to enhance more security levels and also to preserve the cancelable face features, an RSA based encryption-decryption algorithm has been introduced. The proposed system has been tested using four benchmark face databases: CASIA-FACE-v5, IITK, CVL, and FERET, and performance are obtained as correct recognition rate and equal error rate. The performance are compared to the state-of-the-art methods for the superiority of the proposed feature extraction technique and individual performance analysis has been performed at all the security levels of the proposed Cancelable FaceHashing Technique. These comparisons show the superiority of the proposed system. INDEX TERMS Cancelable, FaceHashing, feature extraction, encryption, classification. I. INTRODUCTION Nowadays, the most rising technology for person recognition is based on human biometrics traits. Among the various biometric traits face biometric has vast applications, includ- ing surveillance systems, border security, law enforcement, access control, and entertainment systems. Compared to other biometric traits face is easily captured during standing and walking of a person without his/her interaction with the sys- tem. The facial recognition system plays an important role The associate editor coordinating the review of this manuscript and approving it for publication was Jiafeng Xie. in the human perception systems [1] where the eyes, nose, mouth, jaw are very crucial features. The face biometric is more suitable and convenient than the other biometric traits such as Palmprint, Fingerprint, DNA, Signature, and Voice as it has intangible characteristics. The face biometric gives the dynamic features to the authentication system for the large organizations such as in the educational institutions, the offices with thousands of employees, the borders security checking, etc. This recognition system is cheaper than the others biometric system but it suffers from various challeng- ing issues like lighting variations, different emotional expres- sions (anger, happy, sad, surprise, disgust, fear), wearing of VOLUME 8, 2020 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ 105263