Surveying face liveness detection in the deepfake era

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Luo, Licheng

Contributors dc:contributor

• Wang, Gang

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

Statement dc:rights

• Copyright 2022 Licheng Luo

Language dc:language

en, eng

Handle dc:identifier

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

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F115594