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A Dive into Deepfakes

August 2022 Podcast
Shannon Gallagher, Dominic A. Ross

Shannon Gallagher, a data scientist with SEI’s CERT Division, and Dominic Ross, multimedia team lead for the SEI, discuss deepfakes, their exponential growth in recent years, and their increasing technical sophistication and realism.

"It takes more than just technical skills. It takes artistry as well, and you need both to make a deepfake that’s convincing.”

Publisher:

Software Engineering Institute

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Abstract

Shannon Gallagher, a data scientist with SEI’s CERT Division, and Dominic Ross, multimedia team lead for the SEI, discuss deepfakes, their exponential growth in recent years, their increasing technical sophistication and realism, as well as the problems and challenges that they pose for individuals and organizations. Gallagher and Ross also discuss the SEI’s recent research in assessing the technology underlying the creation and detection of deepfakes and understanding current and future threat levels.

About the Speaker

Shannon Gallagher

Shannon Gallagher

Shannon Gallagher is a data scientist in the SEI’s CERT Division. In that role, Gallagher focuses on modeling, uncertainty quantification, and data visualization and leading research to develop a statistical ...

Shannon Gallagher is a data scientist in the SEI’s CERT Division. In that role, Gallagher focuses on modeling, uncertainty quantification, and data visualization and leading research to develop a statistical pipeline to help determine the authenticity of images and videos. Prior to joining the SEI, Gallagher worked as a post-doctoral researcher at the National Institute of Allergy and Infectious Diseases. There she worked on statistical modeling of infectious diseases, competing events analysis for the ACTT-1 COVID-19 trial, and analysis of statistical tests in low event rate settings. Gallagher received a doctoral degree in statistics from Carnegie Mellon University (CMU). While at CMU, Gallagher was a research and teaching assistant and served as president of the Women in Statistics group.

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