Alignment-free row-co-occurrence cancelable palmprint Fuzzy Vault

Abstract

Texture coding approach of palmprint biometric enjoys several merits; however, palmprint texture code suffers from alignment problem during matching, which hinders it from being directly adopted in biometric cryptosystems, such as Fuzzy Vault. On the other hand, Fuzzy Vault itself is plagued by several security and privacy issues if biometric template is left unprotected. In this paper, we proposed two hybrid cancelable palmprint cryptosystems based on palmprint texture code, dubbed row-alone and row-co-occurrence Fuzzy Vaults. To be specific, we blend 2DPalmHash Code (2DPHC), a cancelable biometric scheme, and Fuzzy Vault primitive to jointly protect palmprint templates. In row-alone Fuzzy Vault, we leverage the horizontal displacement tolerance trait of 2DPHC to extract an alignment-free feature set for polynomial projection. We further generalize row-alone Fuzzy Vault to row-co-occurrence Fuzzy Vault to improve the key recovery rate. Besides that, we demonstrate that 2DPHC-based Fuzzy Vault enhances the robustness against several security attacks.