Christie L., Mancuso K., Fedorishin D., Schneider P., Stone A., Oh K.
University at Buffalo, US
Keywords: additive manufacturing, biometrics, dis- parity map, facial spoofing, thermal retention rate
Biometric security systems such as Apple’s FaceID have replaced passwords for mobile device security, leav- ing users susceptible to biometric spoofing attacks. In response, Apple has implemented an anti-spoofing scheme, looking for autonomous ocular movement associated within the retina. This research aims to quantify the effective- ness of 3D printed spoof masks in regards to defeating a biometric anti-spoofing system such as Apple’s iPhone X. 3D facial spoofs were created and tested using the iPhone X through 3D printing techniques and live cast- ing. The 3D printed face masks were created from a 3D image utilizing a volumetric regression network. A series of anti-spoofing techniques were used as testing validation. These techniques range from measuring the thermal retention rate, stereoscopic facial image dispar- ity map comparisons between a live face, and a spoof image, and implementation of multitask cascaded con- volutional network for recognition of key facial features.
Journal: TechConnect Briefs
Volume: TechConnect Briefs 2019
Published: June 17, 2019
Pages: 147 - 150
Industry sector: Advanced Materials & Manufacturing
Topics: 3D Printing, Advanced Manufacturing
ISBN: 978-0-9988782-8-7