The Layer Deepfake Detection is Missing

AI-generated deepfakes and related fraud techniques increasingly bypass identity systems that focus mainly on detecting visual manipulation in images or video. Although liveness checks, presentation attack detection, deepfake models, and device intelligence remain useful, the passage argues that each is insufficient alone because attackers can use virtual cameras, replays, emulators, synthetic streams, and spoofed device fingerprints. It advocates assessing trust through the integrity of an entire interaction, including camera and device behavior over time, user responses, network context, timing, and consistency among session signals. Future identity verification systems are therefore expected to combine continuous, context-aware analysis across these layers, shifting the central question from whether a face appears real to whether the full session credibly reflects a legitimate person using a real device.

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