Abstract
The emergence of new technology has resulted in mass usage of web applications which lets anyone crowd source anything. In the digitized world, using a wide range of online available tools, anyone can modify and edit images. So, it is necessary to ensure the authenticity of the images. Digital forensic techniques are needed to detect tampering and manipulation of images for illegal purposes [8]. This paper proposes a noble image manipulation detection system using neural networks. There are two techniques for identifying manipulated images in this project, the first one is metadata analysis and the second one is using Convolutional Neural Network. The metadata analysis checks the information contained within the image file and looks for tags that relate to faking. Error Level Analysis is used to detect the compression ratio of foreign content in a fake image.
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