2026-09-22T22:12:07Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/115594 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Wang, Gang 2022-05 application/pdf en text Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01 The student, Licheng Luo, accepted the attached license on 2022-04-22 at 12:10. The student, Licheng Luo, submitted this Thesis for approval on 2022-04-22 at 12:11. This Thesis was approved for publication on 2022-04-26 at 15:43. DSpace SAF Submission Ingestion Package generated from Vireo submission #17872 on 2022-11-11 at 12:11:43 Surveying face liveness detection in the deepfake era Luo, Licheng 2022-04-26 Biometrics Liveness Detection Spoofing Face Liveness Detection DeepFake Generation DeepFake Detection Face DeepFakes 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. Thesis eng https://hdl.handle.net/2142/115594 Copyright 2022 Licheng Luo M.S. Thesis Computer Science University of Illinois at Urbana-Champaign Computer Science