Deepfake — Media Authentication Glossary | Danaya

Synthetic media created using deep learning to replace a person's likeness in existing images or video.

What is a Deepfake?

A deepfake is a type of synthetic media where a person's likeness is replaced with someone else's using deep learning techniques. The term combines 'deep learning' and 'fake' and was coined in 2017.

How Deepfakes Work

Deepfakes use neural networks, typically autoencoders or GANs, trained on thousands of images of a target person. The model learns to generate realistic face replacements that match lighting, expression, and head position.

Detection Methods

Deepfakes can be detected through visual artifacts, inconsistent lighting, unnatural blinking patterns, and frequency analysis. Danaya uses multi-model AI analysis to identify deepfakes with high confidence.

Impact and Risks

Deepfakes pose risks to personal privacy, political integrity, and business trust. They can be used for fraud, misinformation, and reputational harm.

Related Terms

Face Swap

A technique that replaces one person's face with another's in photos or videos.

GAN

Generative Adversarial Network — an AI architecture consisting of two neural networks that compete to generate realistic synthetic data.

Synthetic Media

Any media content — image, video, audio, or text — generated or manipulated by AI.