Deep Fake

Deepfakes, synthetic media created using AI, pose a significant threat by generating highly realistic yet fabricated content, primarily focusing on audio and video manipulation. Current research emphasizes developing robust detection methods using various approaches, including multimodal frameworks that analyze both visual and auditory cues, and novel architectures like Vision Transformers and Convolutional Neural Networks, often incorporating techniques like self-supervised learning and adversarial training to improve generalization and robustness. The ability to reliably detect deepfakes is crucial for maintaining the integrity of digital media and mitigating the risks of misinformation, fraud, and privacy violations, driving ongoing efforts to improve detection accuracy and address the evolving sophistication of deepfake generation techniques.