Published Paper Details:

Copy-move is one type of attack to falsify digital images where the perpetrators copy several regions of the image and then place it on different parts of the same image to cover the part of the image that exists in the area. Therefore, a method is needed to detect copy-move attacks to find out the level the authenticity of a digital image. Image data is often deliberately carried out processes such as the addition of noise and blurring so that copy-move attacks are more difficult to recognize, so that the input image preprocessing stage is a filtering process to eliminate noise in the input image. Stages of detection of copy-move attacks can be shortened by not doing the preprocessing stage but using reliable methods for interference such as noise and blur. Therefore, reliable copy-move attack detection methods are needed for various input image variations so there is no need for preprocessing stages on input images. In this a method created from the modification of two methods of copy-move attack detection, an effective duplication detection method, is used on disturbing images and effective detection methods that are used on images that have disturbances such as noise and blur. Modification of the method is considered effective because of the tolerance between the features of the two methods used. When the input image is distraction-free, the duplication detection feature will become dominant, while the input image has disturbances such as noise and blur, the robust detection feature will become dominant.