Content Authentication Based on Intrinsic Attributes

Number: 20210209196
Published: 2021-07-08
Filed: 2020-01-08
Assignee: Disney Enterprises, Inc.
Inventors: Arana; Mark, Farre Guiu; Miquel Angel, Drake; Edward C., Accardo; Anthony M.
CPC: G06F21/335; G06F21/44; G06F21/64
Verdict: Set aside content authentication, anti-piracy/business
Source: Google Patents · FreePatentsOnline

Abstract

A system for performing authentication of content based on intrinsic attributes includes a computing platform having a hardware processor and a memory storing a content authentication software code. The hardware processor executes the content authentication software code to receive a content file including digital content and authentication data created based on a baseline version of the digital content, to generate validation data based on the digital content, to compare the validation data to the authentication data, and to identify the digital content as baseline digital content in response to determining that the validation data matches the authentication data based on the comparison. The hardware processor is also configured to execute the content authentication software code to identify the digital content as manipulated digital content in response to determining that the validation data does not match the authentication data based on the comparison.

Background

BACKGROUND

Advances in machine learning have enabled the production of realistic but forged recreations of a person's image or voice, known as “deepfakes” due to the use of deep artificial neural networks for their creation. Deepfakes may be produced without the consent of the person whose image or voice is being used, and may make the person being represented appear to say or do something that they have in fact not said or done. As a result, deepfake manipulated digital content can be used maliciously to spread misinformation.

Due to the widespread popularity of digital content for the distribution of entertainment and news, the effective authentication and management of that content is important to its creators, owners and distributors alike. However, as machine learning solutions continue to improve, deepfakes are and will continue to be difficult to detect. As a result, subtly manipulated or even entirely fake digital content may inadvertently be broadcast or otherwise distributed in violation of contractual agreement or regulatory restrictions, thereby subjecting the content owners and/or distributors to potential legal jeopardy. SUMMARY

There are provided systems and methods for performing authentication of content based on intrinsic attributes, substantially as shown in and/or described in connection with at least one of the figures, and as set forth more completely in the claims.

Claims

1. A system for determining authenticity of content, the system comprising: a computing platform including a hardware processor and a system memory; a content authentication software code stored in the system memory; the hardware processor being configured to execute the content authentication software code to: receive a content file including a digital content and an authentication data, the authentication data created based on a baseline version of the digital content; generate a validation data based on the digital content; compare the validation data to the authentication data; identify the digital content as a baseline digital content, in response to determining that the validation data matches the authentication data based on the comparing; and identify the digital content as a manipulated digital content, in response to determining that the validation data does not match the authentication data based on the comparing. || 11. A method for use by a system for determining authenticity of content, the system including a computing platform having a hardware processor and a system memory storing a content authentication software code, the method comprising: receiving, by the content authentication software code executed by the hardware processor, a content file including a digital content and an authentication data, the authentication data created based on a baseline version of the digital content; generating, by the content authentication software code executed by the hardware processor, a validation data based on the digital content; comparing, by the content authentication software code executed by the hardware processor, the validation data to the authentication data; identifying the digital content as a baseline digital content, by the content authentication software code executed by the hardware processor, in response to determining that the validation data matches the authentication data based on the comparing; and identifying the digital content as a manipulated digital content, by the content authentication software code executed by the hardware processor, in response to determining that the validation data does not match the authentication data based on the comparing.