Identifying Fake Images Through CNN Based Classification Using FIDAC

Image forgery is the tampering of digital photos. Because of the ever-evolving technology, creating fake images is no longer difficult. Many researchers have provided different solutions for the detection of image forgery. In this paper, we propose our model that uses CNN for classification after being fed with ELA preprocessed images to detect image forgery, and we also introduce our created dataset - FIDAC (Forged Images Detection And Classification), which consists of original camera-clicked images along with their tampered version. Furthermore, we conducted an experimental analysis wherein we compared our proposed CNN model with famous pre-defined models on various datasets combinations.