Technique to generate face and palm vein-based fuzzy vault for multi-biometric cryptosystem

Abstract

Template security of biometric systems is a vital issue and needs critical focus. The importance lies in the fact that unlike passwords, stolen biometric templates cannot be revoked. Hence, the biometric templates cannot be stored in plain format and needs strong protection against any forgery. In this paper, we present a technique to generate face and palm vein-based fuzzy vault for multi-biometric cryptosystem. Here, initially the input images are pre-processed using various processes to make images fit for further processing. In our proposed method, the features are extracted from the processed face and palm vein images by finding out unique common points. The chaff points are added to the already extracted points to obtain the combined feature vector. The secret key points which are generated based on the user key input (by using proposed method) are added to the combined feature vector to have the fuzzy vault. For decoding, the multi-modal biometric template from palm vein and face image is constructed and is combined with the stored fuzzy vault to generate the final key. Finally, the experimentation is conducted using the palm vein and face database available in the CASIA and JAFFE database. The evaluation metrics employed are FMR (False Match Ratio) and GMR (Genuine Match Ratio). From the metric values obtained for the proposed system, we can infer that the system has performed well.

An Efficient Confidence Interval-Based Dual-Key Fuzzy Vault Scheme for Operator Authentication of Autonomous Unmanned Aerial Vehicles

“…In addition to fingerprints, the fuzzy vault for variable biometrics such as faces, irises, signatures, and palmprints has also been proposed [19][20][21][22][23][24][25]. To improve it for template protection, some researchers have extensively studied applying (1) cancellation with periodic transformation, (2) multimodal with more than two biometrics such as fingerprints, hand veins, face, palm veins, and so on, (3) lattice masks for providing several requirements (e.g., diversity and revocability) without the error correcting code, (4) smart card environments considering automatic fingerprint alignment, verification accuracy, template size, and (5) chaotic system-based multimodal considering the forgery, a significant difference of intra-class, and the security of unimodal biometric leakage [26][27][28][29][30][31][32].…”