IFS TC Webinar: 8 December 2021, by Teddy Furon

The talk conveys a vision of Machine Learning Security based on Information Forensics and Security. In a nutshell, the IFS community protects three cardinal values (confidentiality, integrity, and property) of informative

content, be it a transmitted signal (physical layer), an image (watermarking), or some text (fake news detection), for instance. To what extend can we cast this framework onto Machine Learning? We will see that it makes sense for some scenarios (where we briefly summarize the state-of-the-art) although not covering all threats on Machine Learning.

Currently, he is a researcher employed by INRIA, with the LinkMedia team headed by Laurent Amsaleg. His fields of interest are digital watermarking, passive fingerprinting (a.k.a., traitor tracing), security of Content Based Image Retrieval and more broadly security issues related to multimedia content. From 1998 to 2001, he was a research engineer in the Security Lab of THOMSON multimedia, Rennes, France, working on digital watermarking in the framework of copy protection. He continued working in this field as a postdoctoral researcher at the TELE Lab of the Universite Catholique de Louvain, Louvain-la Neuve, Belgium. From September 2008 to January 2010, he worked in the Security Labs of Technicolor.