Title: Design a modern scheme for machine learning-based detection of image forgery

Authors: Emir Mahmood Kalik; Ayad Hasan Adhab

Addresses: Directorate General of Education Wasit, Ministry of Education Iraq, 52001, Kut, Iraq ' Directorate General of Education Wasit, Ministry of Education Iraq, 52001, Kut, Iraq

Abstract: The rapid growth and development of information technology have led to the emergence of numerous methods that are used for digital image forgery. Thus, manipulating digital images to achieve a negative or positive purpose has become easy. The use of advanced methods in forgery has increased the difficulty of detecting the nature of the images, whether they are original or forged, especially when using classical methods. Therefore, many researchers are interested in this field, making it a popular research direction for researchers. In this paper, we will introduce an intelligent approach to designing a method for digital image forgery detection by using machine learning. This proposal seeks to train an intelligent model to discern between altered and original images by examining the essential features of the images. The results demonstrated that it achieved superior performance and high accuracy when it came to detecting forgeries in digital images.

Keywords: CNN; convolutional neural network; DRL; deep reinforcement learning; forgery; image detection; manipulation.

DOI: 10.1504/IJDATS.2026.151638

International Journal of Data Analysis Techniques and Strategies, 2026 Vol.18 No.1, pp.41 - 56

Received: 18 Jan 2024
Accepted: 19 May 2024
Published online: 11 Feb 2026 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article