Amazon Technologies, Inc.

Xiang Xu

Joseph Patrick Tighe

Jonathan Wu

Zheng Zhang

Hao Chen

Wei Xia

Yuanjun Xiong

Hao Zhou

Mingze Xu

Tianchen Zhao

Systems and techniques are disclosed for authorizing users based on biometric data. Images are collected from an authorized user are used to generate three-dimensional representations of the user that are stored for use in authorization operations. Images accompanying a request for authorization are first processed using liveness detection operations and then, if the images are associated with a live person, a three-dimensional representation of the person is generated using the images. If a correspondence to a verified user's three-dimensional representation is identified for the three-dimensional representation of the person requesting authorization, the request is granted.

Mobile device user authorization system

Techniques for liveness detection based on gesture validation, facial expression analysis, and concurrency validation. The techniques include selecting a color light pattern challenge and sending the color light pattern challenge to a personal computing device for display on a display screen of the personal computing device. A set of target images (video) is received by a liveness detection service in a provider network from the personal computing device as a response to the challenge. The liveness detection service analyzes the set of target images for macro-facial expression and micro-facial expressions. A liveness determination is made by the liveness detection service as to whether the user of the personal computing device is a live genuine user or an impersonated user based on the analysis of the macro and micro-facial expressions detected in the set of target images.

Liveness detection based on gesture validation, facial expression analysis, and concurrency validation

Techniques for liveness detection using a motion, face, and context cues. The techniques can be implemented to prevent against successful presentation attacks, video injection attacks, and deepfake attacks. In some examples, the techniques encompass receiving a set of video frames from a personal computing device. A first liveness determination can be made using a motion-based model based on the received video frames. A second liveness determination can be made using a face-based model based on the received video frames. A third liveness determination can be made using a context-based model based on the received video frames. A final liveness determination can be made based on the first, second and third liveness determinations.

Liveness detection based on motion, face, and context cues

A system for evaluating a biometric authorization system is described. The biometric authorization system is configured to apply a facial recognition model to image data to make an authorization determination based on detection of synthesized image data and based on matching a reference image to the image data. The system is also configured to execute one or more synthetic image data attack protocols to evaluate the biometric authorization system. The system also generates, according to one or more synthetic image data generation techniques, an evaluation set of image data comprising synthesized representations of a target and sends one or more authorization requests using the evaluation set of image data to the biometric authorization system. The system generates an evaluation of the biometric authorization system for synthetic image data attack analysis based on respective responses to the one or more authorization requests received from the biometric authorization system.

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New Hyde Park, NY, United States of America

Xiang Xu