SkullConduct: Biometric User Identification on Eyewear Computers Using Bone Conduction Through the Skull
Stefan Schneegass, Youssef Oualil, Andreas Bulling

Abstract:
Secure user identification is important for the increasing number of eyewear computers but limited input capabilities pose significant usability challenges for established knowledge-based schemes, such as passwords or PINs. We present SkullConduct, a biometric system that uses bone conduction of sound through the users skull as well as a microphone readily integrated into many of these devices, such as Google Glass. At the core of SkullConduct is a method to analyze the characteristic frequency response created by the users skull using a combination of Mel Frequency Cepstral Coefficient (MFCC) features as well as a computationally light-weight 1NN classifier. We report on a controlled experiment with 10 participants that shows that this frequency response is person-specific and stable — even when taking off and putting on the device multiple times — and thus serves as a robust biometric. We show that our method can identify users with 97.0% accuracy and authenticate them with an equal error rate of 6.9%, thereby bringing biometric user identification to eyewear computers equipped with bone conduction technology.

ACM DL: dl.acm.org/citation.cfm?id=2858152
DOI: dx.doi.org/10.1145/2858036.2858152

— chi2016.acm.org/wp/