It's All In The (Deepfake) Experience with Siwei Lyu

To The Point - Cybersecurity

This week we catch up with Dr. Siwei Lyu, a SUNY Empire Innovation Professor and founding Co-Director of Center for Information Integrity (CII) at the University at Buffalo, State University of New York. Siwei breaks down the deepfake experience, both the good and the misleading aspects of the technology. He shares insights on techniques researchers are developing to detect deepfakes, including GAN (Generative Adversarial Network) detected artifacts that produce tell-tale deepfake signs – if you know where to look. He also delves into the area of audio deepfakes and the sophistication of the human auditory system that makes this pathway a tough one to win. And, fun fact, to learn more about Siwei’s research contributions be sure to Google “DeepFake-o-meter”!

Dr. Siwei Lyu, SUNY Empire Innovation Professor at the University at Buffalo

Dr. Siwei Lyu received his B.S. degree (Information Science) in 1997 and his M.S. degree (Computer Science) in 2000, both from Peking University, China. He received his Ph.D. degree in Computer Science from Dartmouth College in 2005. From 1998 to 2000, he worked at the Founder Research and Development Center (Beijing, China) as a Software Engineer. From 2000 to 2001, he worked at Microsoft Research Asia (then Microsoft Research China) as an Assistant Researcher. From 2005 to 2008, he was a Post-Doctoral Research Associate at the Howard Hughes Medical Institute and the Center for Neural Science of New York University. Starting in 2008, he is Assistant Professor at the Computer Science Department of University at Albany, State University of New York. Dr. Lyu is the recipient of the Alumni Thesis Award of Dartmouth College in 2005, IEEE Signal Processing Society Best Paper Award in 2010, and the NSF CAREER Award in 2010. He has authored one book, and held two U.S. and one E.U. patents. He has published more than 50 conference and journal papers in the research fields of natural image statistics, digital image forensics, machine learning and computer vision. For links and resources discussed in this episode, please visit our show notes at https://www.forcepoint.com/govpodcast/e180