Protecting world leaders against deep fakes using facial, gestural, and vocal mannerisms

Author:

Boháček Matyáš1,Farid Hany2

Affiliation:

1. Gymnasium of Johannes Kepler 169 00 Prague, Czech Republic

2. Department of Electrical and Computer Sciences, School of Information, University of California, Berkeley, CA 94708

Abstract

Since their emergence a few years ago, artificial intelligence (AI)-synthesized media—so-called deep fakes—have dramatically increased in quality, sophistication, and ease of generation. Deep fakes have been weaponized for use in nonconsensual pornography, large-scale fraud, and disinformation campaigns. Of particular concern is how deep fakes will be weaponized against world leaders during election cycles or times of armed conflict. We describe an identity-based approach for protecting world leaders from deep-fake imposters. Trained on several hours of authentic video, this approach captures distinct facial, gestural, and vocal mannerisms that we show can distinguish a world leader from an impersonator or deep-fake imposter.

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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1. Face Omron Ring: Proactive defense against face forgery with identity awareness;Neural Networks;2024-12

2. Human detection of political speech deepfakes across transcripts, audio, and video;Nature Communications;2024-09-02

3. Deepfake Technology and Its Implications for Influencer Marketing;Advances in Information Security, Privacy, and Ethics;2024-07-26

4. Training-Free Deepfake Voice Recognition by Leveraging Large-Scale Pre-Trained Models;Proceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security;2024-06-24

5. An MSDCNN-LSTM framework for video frame deletion forensics;Multimedia Tools and Applications;2024-02-12

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