The current development status of deepfake detection technology is introduced, its principles and methods are presented in detail, and researchers look ahead to its future development directions.
In recent years, with the rapid development of deep learning and computer vision technology, the forgery technology of images and videos has become increasingly mature, posing new challenges to information security and social stability. Behind the re-evolution of deepfake lies the rampant proliferation of fake content, which is used for election tampering, identity fraud, fraud, spreading fake news, and so on. To address these challenges, researchers are constantly exploring and developing image-based deepfake detection techniques, which aim to effectively identify and prevent deepfake content in images and videos. This article will introduce the current development status of deepfake detection technology, present its principles and methods in detail, and look ahead to its future development directions.