Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision

Recently, artificial intelligence has been successfully used in fields, such as computer vision, voice, and big data analysis. However, various problems, such as security, privacy, and ethics, also occur owing to the development of artificial intelligence. One such problem are deepfakes. Deepfake is...

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Autores principales:	Gihun Lee, Mihui Kim
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	deepfake computer vision the rate of change Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/63d123cb79934211bfc8a232865d30d0
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id	oai:doaj.org-article:63d123cb79934211bfc8a232865d30d0
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spelling	oai:doaj.org-article:63d123cb79934211bfc8a232865d30d02021-11-11T19:18:27ZDeepfake Detection Using the Rate of Change between Frames Based on Computer Vision10.3390/s212173671424-8220https://doaj.org/article/63d123cb79934211bfc8a232865d30d02021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7367https://doaj.org/toc/1424-8220Recently, artificial intelligence has been successfully used in fields, such as computer vision, voice, and big data analysis. However, various problems, such as security, privacy, and ethics, also occur owing to the development of artificial intelligence. One such problem are deepfakes. Deepfake is a compound word for deep learning and fake. It refers to a fake video created using artificial intelligence technology or the production process itself. Deepfakes can be exploited for political abuse, pornography, and fake information. This paper proposes a method to determine integrity by analyzing the computer vision features of digital content. The proposed method extracts the rate of change in the computer vision features of adjacent frames and then checks whether the video is manipulated. The test demonstrated the highest detection rate of 97% compared to the existing method or machine learning method. It also maintained the highest detection rate of 96%, even for the test that manipulates the matrix of the image to avoid the convolutional neural network detection method.Gihun LeeMihui KimMDPI AGarticledeepfakecomputer visionthe rate of changeChemical technologyTP1-1185ENSensors, Vol 21, Iss 7367, p 7367 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	deepfake computer vision the rate of change Chemical technology TP1-1185
spellingShingle	deepfake computer vision the rate of change Chemical technology TP1-1185 Gihun Lee Mihui Kim Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision
description	Recently, artificial intelligence has been successfully used in fields, such as computer vision, voice, and big data analysis. However, various problems, such as security, privacy, and ethics, also occur owing to the development of artificial intelligence. One such problem are deepfakes. Deepfake is a compound word for deep learning and fake. It refers to a fake video created using artificial intelligence technology or the production process itself. Deepfakes can be exploited for political abuse, pornography, and fake information. This paper proposes a method to determine integrity by analyzing the computer vision features of digital content. The proposed method extracts the rate of change in the computer vision features of adjacent frames and then checks whether the video is manipulated. The test demonstrated the highest detection rate of 97% compared to the existing method or machine learning method. It also maintained the highest detection rate of 96%, even for the test that manipulates the matrix of the image to avoid the convolutional neural network detection method.
format	article
author	Gihun Lee Mihui Kim
author_facet	Gihun Lee Mihui Kim
author_sort	Gihun Lee
title	Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision
title_short	Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision
title_full	Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision
title_fullStr	Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision
title_full_unstemmed	Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision
title_sort	deepfake detection using the rate of change between frames based on computer vision
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/63d123cb79934211bfc8a232865d30d0
work_keys_str_mv	AT gihunlee deepfakedetectionusingtherateofchangebetweenframesbasedoncomputervision AT mihuikim deepfakedetectionusingtherateofchangebetweenframesbasedoncomputervision
_version_	1718431587697164288

Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision

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