Creating, Weaponizing, and Detecting Deep Fakes

Authors: 

Hany Farid, Professor, UC Berkeley

Abstract: 

The past few years have seen a startling and troubling rise in the fake-news phenomena in which everyone from individuals to nation-sponsored entities can produce and distribute mis-information. The implications of fake news range from a mis-informed public to an existential threat to democracy, and horrific violence. At the same time, recent and rapid advances in machine learning are making it easier than ever to create sophisticated and compelling fake images. videos, and audio recordings, making the fake-news phenomena even more powerful and dangerous. I will provide an overview of the creation of these so-called deep-fakes, and I will describe emerging techniques for detecting these fakes.

Hany Farid, Professor, UC Berkeley

Hany Farid is a Professor in the department of Electrical Engineering & Computer Science and the School of Information at UC Berkeley. His research focuses on digital forensics, image analysis, and human perception. Hany received my undergraduate degree in Computer Science and Applied Mathematics from the University of Rochester in 1989, my M.S. in Computer Science from SUNY Albany, my Ph.D. in Computer Science from the University of Pennsylvania in 1997, followed by a two-year post-doctoral fellowship in Brain and Cognitive Sciences at MIT. He was on the faculty at Dartmouth College from 1999-2019 and joined the faculty at UC Berkeley in 2019. Hany is the the recipient of an Alfred P. Sloan Fellowship, a John Simon Guggenheim Fellowship, and is a Fellow of the National Academy of Inventors.

BibTeX
@conference {236681,
author = {Hany Farid},
title = {Creating, Weaponizing, and Detecting Deep Fakes},
year = {2019},
address = {Santa Clara, CA},
publisher = {{USENIX} Association},
}