Comprehensive framework for detecting synthetic media, analyzing manipulation artifacts, and establishing media provenance in the post-empirical era.
Deepfakes are synthetic media created using deep learning techniques—primarily Generative Adversarial Networks (GANs), Diffusion Models, and Autoencoders—to generate or manipulate audiovisual content with a high degree of realism. The term combines "deep learning" and "fake."
| Face Swap | Autoencoders, GANs | Replace one person's face with another in video | | Face Reenactment | 3D Morphable Models | Animate a face with another person's expressions | | Voice Clone | Text-to-Speech, Vocoder | Generate speech in someone's voice from text [[20]](#references) |
Мультимодальная аутентификация мультимедиа и криминалистика дипфейков. Анализ PRNU, классификация IGH, обнаружение DQ, семантическая криминалистика и осмысление, дополненное LLM, для постэмпирической эпохи. Источник: dirnbauer/webconsulting-skills.