deepfake

Deepfakes are AI-generated synthetic videos that realistically swap faces or manipulate expressions using deep learning. Detection is an ongoing arms race as generation techniques improve. Early deepfakes used autoencoders and GANs while modern ones use diffusion models and neural rendering. Detection methods include analyzing inconsistencies in lighting blinking patterns facial landmarks temporal coherence and compression artifacts. Biological signals like pulse detection from subtle color changes can reveal fakes. Blockchain-based authenticity verification and digital signatures help establish provenance. The technology raises concerns about misinformation political manipulation and non-consensual content. Positive applications include film production dubbing accessibility and historical recreation. Platforms use AI detectors watermarking and content authentication. Research focuses on generalizable detection that works across generation methods. As generation improves detection must evolve requiring continuous model updates and multi-modal analysis combining visual audio and metadata signals.