Date of Award

1-1-2020

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Computer Science

Content Description

1 online resource (xi, 125 pages) : color illustrations.

Dissertation/Thesis Chair

Siwei Lyu

Committee Members

Ming-ching Chang, Chengjiang Long

Keywords

Artificial intelligence, Human face recognition (Computer science), Digital video, Computer security, Image processing, Disinformation

Subject Categories

Computer Sciences

Abstract

The recent advances in deep learning and the availability of vast volume of online personal images and videos have drastically improved the reality of synthesized faces in images and videos. While there are interesting and creative applications of the AI face synthesis systems, they can also be weaponized, as it can create the illusions of a person's presence and activities that do not occur in reality, which results in serious political, social, financial, and legal consequences. Therefore, it is of great importance to develop effective method to expose the AI-synthesized faces. In this thesis, a set of our recent efforts on detecting and protecting against AI-synthesized faces is described. For detection, the signals such as facial landmark difference, eye blinking and head pose inconsistency, and face warping artifacts are utilized to spot the synthesized faces respectively. Moreover, a new large-scale challenging synthesized face dataset with highly realistic quality is constructed, to further improve the development of detection. For protecting against the AI-synthesized faces, a proactive method is proposed to prevent people from being the victim of AI systems by disturbing the training process. Several experiments are conducted to demonstrate the effectiveness of our works.

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