Deepfakes
Technology, Threats, and Regulation
Deepfakes are synthetic media created using deep learning techniques (primarily Generative Adversarial Networks or GANs, and more recently diffusion models) that can generate realistic but fabricated images, audio, and video. They pose serious threats to individual privacy, democratic processes, and national security through misinformation, impersonation, and non-consensual intimate imagery.
- Technology: GANs (introduced by Ian Goodfellow, 2014) and diffusion models (Stable Diffusion, DALL-E, Midjourney) are the primary architectures
- Threats: Political misinformation (election manipulation), non-consensual intimate imagery, financial fraud (CEO impersonation), identity theft
- Global regulation: EU AI Act (2024) classifies deepfakes as "limited risk" requiring transparency obligations; US has state-level laws (e.g., California, Texas)
- India's approach: No standalone deepfake legislation; regulation through IT Act and IT Rules amendments
- Sections 66C (identity theft), 66D (cheating by personation using computer resource), and 66E (violation of privacy) of the IT Act are used against deepfake-related offences
● Tracked since February 10, 2026 · last seen June 11, 2026 · updates as the daily brief publishes
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