SkullConduct: Biometric User Identification on Eyewear Computers Using Bone Conduction Through the Skull
Art der Publikation: Beitrag in Sammelwerk
| Autor(en): | Stefan Schneegass, Youssef Oualil; Bulling, Andreas |
|---|---|
| Titel des Sammelbands: | Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI '16) |
| Seiten: | 1379-1384 |
| Verlag: | ACM |
| Ort(e): | New York, USA |
| Veröffentlichung: | 2016 |
| ISBN: | 978-1-4503-3362-7 |
| Digital Object Identifier (DOI): | doi:10.1145/2858036.2858152 |
| Volltext: | SkullConduct: Biometric User Identification on Eyewear Computers Using Bone Conduction Through the Skull (1,47 MB) |
| Zitation: | Download BibTeX |
Kurzfassung
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 user's 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 user's 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.