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Dodis et al. proposed an improved version of the fuzzy vault scheme, one ofthe most popular primitives used in biometric cryptosystems, requiring lessstorage and leaking less information. Recently, Blanton and Aliasgari haveshown that the relation of two improved fuzzy vault records of the sameindividual may be determined by solving a system of non-linear equations.However, they conjectured that this is feasible for small parameters only. Inthis paper, we present a new attack against the improved fuzzy vault schemebased on the extended Euclidean algorithm that determines if two records arerelated and recovers the elements by which the protected features, e.g., thebiometric templates, differ. Our theoretical and empirical analysisdemonstrates that the attack is very effective and efficient for practicalparameters. Furthermore, we show how this attack can be extended to fullyrecover both feature sets from related vault records much more efficiently thanpossible by attacking each record individually. We complement this work byderiving lower bounds for record multiplicity attacks and use these to showthat our attack is asymptotically optimal in an information theoretic sense.Finally, we propose remedies to harden the scheme against record multiplicityattacks.

Security of the Improved Fuzzy Vault Scheme in the Presence of Record Multiplicity (Full Version)