Webology (ISSN: 1735-188X) Volume 19, Number 2, 2022 6124 http://www.webology.org Efficient Analysis Of Manipulated Image Processing Gavendra Singh 1 , Faizur Rashid 2 , Afendi Abdi 3 Department of Software Engineering 1,3 Department of Computer Science 2 College of computing and Informatics Haramaya University 138, Dire Dawa. Ethiopia. Abstract The fast progress in engineered image generation and manipulation has now gone to a point where it raises huge worries on the suggestion on the public. Best-case scenario, this prompt lost trust in advanced content, yet it may even bring about additional mischief by spreading false data and the making of phony news. In this paper, we look at the authenticity of best-in-class Image detections, and that it is so hard to identify them - either consequently or by people. Specifically, we center on Deep Fakes, copy-move, splicing, resembling and statistical. As noticeable delegates for image categorization. Traditional image forensics techniques are usually not well suited to blur images due to the compression that strongly degrades the data. Thus, this paper follows a deep learning approach and presents two networks, both with a low number of layers to focus on the macroscopic properties of images. We make the greater part a million controlled images individually for each approach. The subsequent freely accessible dataset is at any rate a request for greatness bigger than similar other options and it empowers us to prepare information driven phony locators in an administered manner. We will show that the utilization of extra space explicit learning improves imitation identification to an exceptional precision. Keywords: Deep Fakes, copy-move, splicing 1. Introduction From the early days, an image has normally been accepted as proof of the amount of the depicted event. Computer becoming more customary in business and other fields, accepting digital image as an official document has become a common practice. The accessibility of low-cost hardware and software tools makes it easy to create, alter, and manipulate digital images with no understandable traces of having been subjected to any of these operations. As a result, we are hastily reaching a situation where one can no longer take the reliability and validity of digital images for granted. This trend undermines the integrity of digital images presented as evidence in