Secure Fingerprint Identification of High Accuracy

The increasing availability and use of biometric data for authentication and other purposes leads to situations when sensitive biometric data is to be handled or used in computation by entities who may not be fully trusted or otherwise authorized to have full access to such data. This calls for mechanisms of provably protecting biometric data while still allowing the computation to take place. In this work, we treat the problem of privacypreserving matching of two fingerprints, which can be used for secure fingerprint authentication and identification. We utilize traditional minutia-based representation of fingerprints that leads to the most discriminative (i.e., accurate) fingerprint comparisons. Unlike prior work, we design a data-oblivious algorithm that results in the most accurate outcome of fingerprint matching through a more complex minutia pairing approach based on maximum flow in bipartite graphs. This algorithm then leads to secure fingerprint matching solutions of high security standards. The complexity of our solution is higher than those of some other available protocols, but nevertheless we show that our techniques still efficiently compare two fingerprints with provable security guarantees. That is, they run in a similar amount of time to those with simpler matching mechanisms which are not guaranteed to find the best matching.