Invention Grant
- Patent Title: Authenticator-integrated generative adversarial network (GAN) for secure deepfake generation
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Application No.: US17356116Application Date: 2021-06-23
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Publication No.: US12248556B2Publication Date: 2025-03-11
- Inventor: Ilke Demir , Carl S. Marshall , Satyam Srivastava , Steven Gans
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: JAFFREY WATSON MENDONSA & HAMILTON LLP
- Main IPC: G06F21/00
- IPC: G06F21/00 ; G06F21/44 ; G06N3/08

Abstract:
An apparatus to facilitate an authenticator-integrated generative adversarial network (GAN) for secure deepfake generation is disclosed. The apparatus includes one or more processors to: generate, by a generative neural network, samples based on feedback received from a discriminator neural network and from an authenticator neural network, the generative neural network aiming to trick the discriminator neural network to identify the generated samples as real content samples; digest, by the authenticator neural network, the real content samples, the generated samples from the generative neural network, and an authentication code; embed, by the authenticator neural network, the authentication code into the generated samples from the generative neural network by contributing to a generator loss provided to the generative neural network; generate, by the generative neural network, content comprising the embedded authentication code; and verify, by the authenticator neural network, the content based on the embedded authentication code.
Public/Granted literature
- US20210319090A1 AUTHENTICATOR-INTEGRATED GENERATIVE ADVERSARIAL NETWORK (GAN) FOR SECURE DEEPFAKE GENERATION Public/Granted day:2021-10-14
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