Surveying face liveness detection in the deepfake era

Luo, Licheng

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https://hdl.handle.net/2142/115594 Copy

Description

Title

Surveying face liveness detection in the deepfake era

Author(s)

Luo, Licheng

Issue Date

2022-04-26

Director of Research (if dissertation) or Advisor (if thesis)

Wang, Gang

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Biometrics
• Liveness Detection
• Spoofing
• Face Liveness Detection
• DeepFake Generation
• DeepFake Detection
• Face
• DeepFakes

Abstract

Face authentication systems are used more and more in different applications. However, their security relies on the face liveness detection method they use. With the advent of deepfake technologies that make modifications like face swapping easier than ever, there is an urgent need to understand what threats deepfakes pose to liveness detection and explore how to mitigate those threats. In this thesis, I first survey existing methods for face liveness detection. Then I will survey deepfake technologies in terms of its generation and detection methods to provide a comprehensive overview, with a particular focus on the technologies that could be used for practical attacks against liveness detection. I discuss the implications and conduct a case study on a commercial face liveness detection system to show how one can make such systems secure in practice. Finally, I would conclude with open research directions for future work.

Graduation Semester

2022-05

Type of Resource

Thesis

Copyright and License Information

Copyright 2022 Licheng Luo

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