Multi-biometric systems are known to be universal and more accurate in biometric recognition. However, the storage of multiple biometric templates as separate entities pose major threats to user privacy and system security. Therefore, we propose to fuse multiple biometric modalities at the feature level in order to obtain an integrated template and to secure the fused templates using a hybrid template protection method. The proposed method is made out of a feature transformation technique known as Random Tiling and an equal-probable 2^N discretization scheme. The former enables the revocability of the template and the latter converts the feature elements into binary representations according to the area under the genuine interval curve, in order to offer better privacy protection to the template. Our experimental results show that the proposed multi-biometric template protection scheme demonstrates better verification results as compared to their unibiometric counterparts while preserving template security.
