Image authentication system using deep learning / Muhammad Faisal Amer Faudzli and Muhamad Arif Hashim
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 r...
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| Main Authors: | , |
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| Format: | Book Section |
| Language: | en |
| Published: |
College of Computing, Informatics and Media, UiTM Perlis
2023
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/100741/1/100741.pdf https://ir.uitm.edu.my/id/eprint/100741/ |
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| Summary: | 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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