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Cancelable biometric schemes generate secure biometric templates by combininguser specific tokens and biometric data. The main objective is to createirreversible, unlinkable, and revocable templates, with high accuracy inmatching. In this paper, we cryptanalyze two recent cancelable biometricschemes based on a particular locality sensitive hashing function, index-of-max(IoM): Gaussian Random Projection-IoM (GRP-IoM) and Uniformly RandomPermutation-IoM (URP-IoM). As originally proposed, these schemes were claimedto be resistant against reversibility, authentication, and linkability attacksunder the stolen token scenario. We propose several attacks against GRP-IoM andURP-IoM, and argue that both schemes are severely vulnerable againstauthentication and linkability attacks. We also propose better, but not yetpractical, reversibility attacks against GRP-IoM. The correctness and practicalimpact of our attacks are verified over the same dataset provided by theauthors of these two schemes.

A Cryptanalysis of Two Cancelable Biometric Schemes based on Index-of-Max Hashing