Facial biohashing based user-device physical unclonable function for bring your own device security

Bring your own device (BYOD) is gaining popularity. Using multifarious personal devices in the workplace to perform work-related tasks brings new challenges to trust and privacy management. Existing authentication schemes usually target at user or device separately, while the BYOD system needs to ensure that only the authorized user with the trusted devices can be given access. This paper presents a novel biohashing based user-device physical unclonable function (UD PUF) to provide a bipartite authentication of both user and device for the BYOD system. Biometric features are extracted as user identity while PUF endows the device with an inseparable and unclonable “fingerprint”. Biohashing acts as an intermediary between these two incoherent macroscopic biometric and microscopic silicon entropy sources for security enhancement. The concept is demonstrated using a 64 × 64 image sensor PUF simulated in 180nm 3.3 V CMOS technology, and the ORL and yale databases of faces. Our preliminary experimental results showed that a genuine (user, device, challenge) combination exhibits a very low equal error rate of 0.032, and tampering of any elements of the tuple will cause the hamming distance between the “live” and enrolled templates to have nearly random distribution.