Article: Application of artificial intelligence: methods to detect the image changes in social media Journal: International Journal of Electronic Security and Digital Forensics (IJESDF) 2026 Vol.18 No.8 pp.1 - 15 Abstract: Active and passive methods are the two basic techniques to image modification detection that are described in the existing body of literature. In contrast to passive approaches, active techniques are proactive in nature, since they embed structures into photographs in order to enable future authenticity verification. The outputs from various networks are then fused together via the concatenation in order to determine whether or not the picture has been manipulated. This results in a complete detection framework that is more effective than the individual approaches that make up the framework. Our study presents a one-of-a-kind dataset that is the result of the combination of four datasets that are freely accessible to the public. This set of data includes photos that have been changed naturally and are very close to what happened in real life. It demonstrates improved generalisation across a wide range of data manipulation methods. Inderscience Publishers - linking academia, business and industry through research

Title: Application of artificial intelligence: methods to detect the image changes in social media

Authors: Yan Gao

Addresses: Department of Media, Zhengzhou University of Economics and Business, Zhengzhou Henan, 451191, China

Abstract: Active and passive methods are the two basic techniques to image modification detection that are described in the existing body of literature. In contrast to passive approaches, active techniques are proactive in nature, since they embed structures into photographs in order to enable future authenticity verification. The outputs from various networks are then fused together via the concatenation in order to determine whether or not the picture has been manipulated. This results in a complete detection framework that is more effective than the individual approaches that make up the framework. Our study presents a one-of-a-kind dataset that is the result of the combination of four datasets that are freely accessible to the public. This set of data includes photos that have been changed naturally and are very close to what happened in real life. It demonstrates improved generalisation across a wide range of data manipulation methods.

Keywords: digital image forensics; convolutional neural network; CNN; deep learning.

DOI: 10.1504/IJESDF.2026.152801

International Journal of Electronic Security and Digital Forensics, 2026 Vol.18 No.8, pp.1 - 15

Received: 02 Sep 2024
Accepted: 20 Nov 2024
Published online: 13 Apr 2026 *

Title: Application of artificial intelligence: methods to detect the image changes in social media

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