Photo Forensics from JPEG Coding Artifacts

Hany Farid

(Berkeley)

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Date: November 14, 2018

Description:

The past few years have seen a startling and troubling rise in the fake-news phenomena in which everyone from individuals to state-sponsored entities produce and distribute mis-information, which is then widely promoted and disseminated on social media. 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 and videos, making the fake-news phenomena even more powerful and dangerous. I will start by providing a broad overview of the field of image and video forensics and then I will describe in detail a suite of image forensic techniques that explicitly detect inconsistencies in JPEG coding artifacts

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