Seeing Your Face Is Not Enough
Yan Li, Yingjiu Li, Qiang Yan, Hancong Kong, Robert Huijie Deng · 2015
Leveraging built-in cameras on smartphones and tablets, face authentication provides an attractive alternative of legacy passwords due to its memory-less authentication process. However, it has an intrinsic vulnerability against the media-based facial forgery (MFF) where adversaries use photos/videos containing victims' faces to circumvent face authentication systems. In this paper, we propose FaceLive, a practical and robust liveness detection mechanism to strengthen the face authentication on mobile devices in fighting the MFF-based attacks. FaceLive detects the MFF-based attacks by measuring the consistency between device movement data from the inertial sensors and the head pose changes from the facial video captured by built-in camera. FaceLive is practical in the sense that it does not require any additional hardware but a generic front-facing camera, an accelerometer, and a gyroscope, which are pervasively available on today's mobile devices. FaceLive is robust to complex lighting conditions, which may introduce illuminations and lead to low accuracy in detecting important facial landmarks; it is also robust to a range of cumulative errors in detecting head pose changes during face authentication.