Image authentication system using deep learning / Muhammad Faisal Amer Faudzli and Muhamad Arif Hashim

Faudzli, Muhammad Faisal Amer and Hashim, Muhamad Arif (2023) Image authentication system using deep learning / Muhammad Faisal Amer Faudzli and Muhamad Arif Hashim. In: Research Exhibition in Mathematics and Computer Sciences (REMACS 5.0). College of Computing, Informatics and Media, UiTM Perlis, pp. 257-258. ISBN 978-629-97934-0-3

Abstract

Using a variety of techniques, image manipulation can be performed not only by commercial editors, but also by criminals and counterfeiters for the goal of counterfeiting. Digital forensic tools are required to detect the manipulation and tampering of images for such unlawful activities. For these reasons, this research offered an algorithm for detecting image manipulation using Convolutional Neural Network (CNN) technique that has produced excellent results in recent studies. In addition, the other purpose was to assess the performance of the developed CNN image authentication system in detecting tampering in images.

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Item Type: Book Section
Creators:
Creators
Email / ID Num.
Faudzli, Muhammad Faisal Amer
UNSPECIFIED
Hashim, Muhamad Arif
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Neural networks (Computer science)
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus > Faculty of Computer and Mathematical Sciences
Page Range: pp. 257-258
Keywords: tampered image, neural network, image classification, deep learning, Convolutional Neural Network (CNN)
Date: 2023
URI: https://ir.uitm.edu.my/id/eprint/100741
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