A Dive into Deepfakes Podcast
Abstract
VIDEO/Podcasts/vlogs This video and all related information and materials ("materials") are owned by Carnegie Mellon University. These materials are provided on an "as-is" "as available" basis without any warranties and solely for your personal viewing and use. You agree that Carnegie Mellon is not liable with respect to any materials received by you as a result of viewing the video, or using referenced websites, and/or for any consequence or the use by you of such materials. By viewing, downloading and/or using this video and related materials, you agree that you have read and agree to our terms of use (http://www.sei.cmu.edu/legal/index.cfm). Today, I am joined by Shannon Gallagher, a data scientist in the CERT Division. Today we are here to talk about our work on DeepFakes, specifically how easy is it to make and detect a deepfake. As we stated in a recently published SEI blog post on this work, there were more than 85,000 harmful deepfake videos detected up to December 2020, with the number doubling every six months since observations began in December 2018. So Deepfakes are definitely a problem for many organizations.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 28, 2022
- Accession Number
- AD1172640
Entities
People
- Dominic Ross
- Shannon Gallagher
Organizations
- Carnegie Mellon University