The Growing Need for Deepfakes Detection in the Age of AI-Generated Media
Parveen Badoni, Muhammad Shahid Dildar, Mohammad Nadeem Ahmed, Abu Sarwar Zamani, Mohammad Rashid Hussain, Manoj Wadhwa · 2025
Deepfakes detection is now a necessity because deep learning methods for producing highly realistic synthetic media are advancing at an alarming rate. These doctored photos, videos, and audio files can mislead their audience, disseminate disinformation, and represent a major security risk. Detection techniques utilize convolutional neural networks, recurrent neural networks, and transformer models to detect minor artifacts, inconsistencies, and unnatural patterns in multimedia content. Methods such as frequency analysis, facial landmark tracking, and adversarial training are used to improve detection accuracy. The ongoing development of generative models requires constant research to create resilient and flexible detection systems that can counter the threats from synthetic media manipulation.