Deepfake hunters. Challenges and technological solutions for detection and authentication

Abstract

In an increasingly digitalized society, deepfakes, which are AI-based technologies, represent a growing challenge. These false multimedia contents can realistically mimic images, videos, and audio, raising concerns about their potential use for manipulation and disinformation. This article explores what deepfakes are, the techniques used to create them, and advanced detection methods, such as convolutional neural networks (CNNs) and generative adversial network (GAN) reconfiguration. It also addresses the importance of digital content authentication through techniques like digital signatures and chain of custody. The article concludes with a reflection on the need for a coordinated response, both technological and legal, to mitigate the risks associated with deepfakes.