公开(公告)号：US20210319240A1

公开(公告)日：2021-10-14

申请号：US17356067

申请日：2021-06-23

Applicant: Intel Corporation

Inventor： Ilke Demir ,  Carl S. Marshall ,  Satyam Srivastava ,  Steven Gans

IPC: G06K9/00 ,  G06N3/08 ,  G06N3/04

Abstract: An apparatus to facilitate generator exploitation for deepfake detection is disclosed. The apparatus includes one or more processors to: alter a generative neural network of a deepfake generator with one or more modifications for deepfake detection; train the generative neural network having the one or more modifications and a discriminative neural network of the deepfake generator, wherein training the generative neural network and the discriminative neural network to facilitate the generative neural network to generate deepfake content comprising the one or more modifications; and communicate identification of the one or more modifications to a deepfake detector to cause the deepfake detector to identify deepfake content generated by the deepfake generator that comprises at least one of the one or more modifications.

公开(公告)号：US12248556B2

公开(公告)日：2025-03-11

申请号：US17356116

申请日：2021-06-23

Applicant: Intel Corporation

Inventor： Ilke Demir ,  Carl S. Marshall ,  Satyam Srivastava ,  Steven Gans

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.

公开(公告)号：US20220004904A1

公开(公告)日：2022-01-06

申请号：US17481475

申请日：2021-09-22

Applicant: Intel Corporation

Inventor： Georg Stemmer ,  Carl Marshall ,  Satyam Srivastava ,  Ilke Demir

IPC: G06N5/04 ,  G06K9/62

Abstract: An apparatus to facilitate deepfake detection models utilizing subject-specific libraries is disclosed. The apparatus includes one or more processors to store a plurality of deepfake detection models corresponding to a plurality of subjects of interest; receive a query to identify whether data pertaining to a target subject of interest is a deepfake, the target subject of interest comprised in the plurality of subjects of interest and associated with a subject identifier (ID); identify a deepfake detection model corresponding to the subject ID; extract features for deepfake detection from the data; input the extracted features to the identified deepfake detection model corresponding to the subject ID; and responsive to an output of the deepfake detection model exceeding a determined deepfake threshold, generate a notification, in response to the query, indicating a possible deepfake attack corresponding to the target subject of interest.

公开(公告)号：US20240144447A1

公开(公告)日：2024-05-02

申请号：US18532273

申请日：2023-12-07

Applicant: Intel Corporation

Inventor： Anthony Daniel Rhodes ,  Ilke Demir

IPC: G06T5/70 ,  G06V10/30 ,  G06V10/32 ,  G06V10/46

CPC classification number: G06T5/70 ,  G06V10/30 ,  G06V10/32 ,  G06V10/462

Abstract: Deep learning models, such as diffusion models, can synthesize images from noise. Diffusion models implement a complex denoising process involving many denoising operations. It can be a challenge to understand the mechanics of diffusion models. To better understand how and when structure is formed, saliency maps and concept formation intensity can be extracted from the sampling network of a diffusion model. Using the input map and the output map of a given denoising operation in a sampling network, a noise gradient map representative of the predicted noise of a given denoising operation can be determined. The noise gradient maps from the denoising operations at different indices can be combined to generate a saliency map. A concept formation intensity value can be determined from a noise gradient map. Concept formation intensity values from the denoising operations at different indices can be plotted.

公开(公告)号：US20240320953A1

公开(公告)日：2024-09-26

申请号：US18677473

申请日：2024-05-29

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Ilke Demir ,  Yali Bian

IPC: G06V10/74 ,  G06V10/46

CPC classification number: G06V10/761 ,  G06V10/462

Abstract: An example apparatus includes interface circuitry, machine-readable instructions, and at least one processor circuit to be programmed by the machine-readable instructions to access a first saliency map and a second saliency map associated with an image dataset, encode pixel-level intensity of the first saliency map, encode pixel-level intensity of the second saliency map, generate a saliency comparison metric based on the pixel-level intensity of the first saliency map and the pixel-level intensity of the second saliency map, and compare spatial properties of the first saliency map and the second saliency map using the saliency comparison metric.

公开(公告)号：US20210319090A1

公开(公告)日：2021-10-14

申请号：US17356116

申请日：2021-06-23

Applicant: Intel Corporation

Inventor： Ilke Demir ,  Carl S. Marshall ,  Satyam Srivastava ,  Steven Gans

IPC: 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.

公开(公告)号：US12125256B2

公开(公告)日：2024-10-22

申请号：US17356067

申请日：2021-06-23

Applicant: Intel Corporation

Inventor： Ilke Demir ,  Carl S. Marshall ,  Satyam Srivastava ,  Steven Gans

IPC: G06N3/08 ,  G06N3/045 ,  G06V10/44 ,  G06V10/764 ,  G06V10/82 ,  G06V40/40

CPC classification number: G06V10/454 ,  G06N3/045 ,  G06N3/08 ,  G06V10/764 ,  G06V10/82 ,  G06V40/40

Abstract: An apparatus to facilitate generator exploitation for deepfake detection is disclosed. The apparatus includes one or more processors to: alter a generative neural network of a deepfake generator with one or more modifications for deepfake detection; train the generative neural network having the one or more modifications and a discriminative neural network of the deepfake generator, wherein training the generative neural network and the discriminative neural network to facilitate the generative neural network to generate deepfake content comprising the one or more modifications; and communicate identification of the one or more modifications to a deepfake detector to cause the deepfake detector to identify deepfake content generated by the deepfake generator that comprises at least one of the one or more modifications.