  Cancelable biometric schemes generate secure biometric templates by combining
user specific tokens and biometric data. The main objective is to create
irreversible, unlinkable, and revocable templates, with high accuracy in
matching. In this paper, we cryptanalyze two recent cancelable biometric
schemes based on a particular locality sensitive hashing function, index-of-max
(IoM): Gaussian Random Projection-IoM (GRP-IoM) and Uniformly Random
Permutation-IoM (URP-IoM). As originally proposed, these schemes were claimed
to be resistant against reversibility, authentication, and linkability attacks
under the stolen token scenario. We propose several attacks against GRP-IoM and
URP-IoM, and argue that both schemes are severely vulnerable against
authentication and linkability attacks. We also propose better, but not yet
practical, reversibility attacks against GRP-IoM. The correctness and practical
impact of our attacks are verified over the same dataset provided by the
authors of these two schemes.
