Deepfake Detection

Deepfake detectors look for statistical artifacts left behind by generation models — texture inconsistencies, unnatural blinking, frequency-domain signatures. Each generation of detectors works well until the next generation of generators trains around it.

The arms race favors generators in the long run, because they have access to detector outputs as part of their training signal.

The complementary strategy is provenance: cryptographically signed content credentials that travel with media from capture through publication. Authentic content carries proof; unsigned content is treated with appropriate skepticism.

Provenance does not detect fakes. It authenticates originals. That asymmetry is what makes it more durable than detection alone.