Detecting Deep Fakes with a Heartbeat

2020-10-01 11:19

In particular, video of a person's face contains subtle shifts in color that result from pulses in blood circulation.

Deep fakes don't lack such circulation-induced shifts in color, but they don't recreate them with high fidelity.

The researchers at SUNY and Intel found that "Biological signals are not coherently preserved in different synthetic facial parts" and that "Synthetic content does not contain frames with stable PPG." Translation: Deep fakes can't convincingly mimic how your pulse shows up in your face.

The inconsistencies in PPG signals found in deep fakes provided these researchers with the basis for a deep-learning system of their own, dubbed FakeCatcher, which can categorize videos of a person's face as either real or fake with greater than 90 percent accuracy.

I expect deep fake programs to become good enough to fool FakeCatcher in a few months.

News URL

https://www.schneier.com/blog/archives/2020/10/detecting-deep-fakes-with-a-heartbeat.html