Paper 2020/1363

Game-Set-MATCH: Using Mobile Devices for Seamless External-Facing Biometric Matching

Shashank Agrawal, Saikrishna Badrinarayanan, Pratyay Mukherjee, and Peter Rindal

Abstract

We use biometrics like fingerprints and facial images to identify ourselves to our mobile devices and log on to applications everyday. Such authentication is internal-facing: we provide measurement on the same device where the template is stored. If our personal devices could participate in external-facing authentication too, where biometric measurement is captured by a nearby external sensor, then we could also enjoy a frictionless authentication experience in a variety of physical spaces like grocery stores, convention centers, ATMs, etc. The open setting of a physical space brings forth important privacy concerns though. We design a suite of secure protocols for external-facing authentication based on the cosine similarity metric which provide privacy for both user templates stored on their devices and the biometric measurement captured by external sensors in this open setting. The protocols provide different levels of security, ranging from passive security with some leakage to active security with no leakage at all. With the help of new packing techniques and zero-knowledge proofs for Paillier encryption - and careful protocol design, our protocols achieve very practical performance numbers. For templates of length 256 with elements of size 16 bits each, our fastest protocol takes merely 0.024 seconds to compute a match, but even the slowest one takes no more than 0.12 seconds. The communication overhead of our protocols is very small too. The passive and actively secure protocols (with some leakage) need to exchange just 16.5KB and 27.8KB of data, respectively. The first message is designed to be reusable and, if sent in advance, would cut the overhead down to just 0.5KB and 0.8KB, respectively.