AN OVERVIEW OF “AI FAKEBUSTER”: A DEEPFAKE DETECTION APP

Abstract: Deepfake leverage machine learning algorithms, particularly Generative Adversarial Networks (GANs), to create highly realistic images, videos, or audio recordings of individuals. By learning from vast datasets, these models can generate media that mimics real-life behavior, expressions, and voices, making them difficult to identify as fake. The primary objective of this project is to develop a Deepfake Detection System that can effectively identify and classify manipulated media using advanced deep learning and computer vision techniques. This system aims to address the security, ethical, and social implications posed by synthetic media by providing a reliable tool for the detection and analysis of deepfakes in both static images and video sequences.

Keywords: Deepfake, Fake Image Detection, Fake Video Detection, Image Dataset, Video Dataset.