Facebook and Twitter earlier this week took down social media accounts associated with the Internet Research Agency, the Russian troll farm that interfered in the U.S. presidential election four years ago, that had been spreading misinformation to up to 126 million Facebook users. Today, Facebook rolled out measures aimed at curbing disinformation ahead of Election Day in November. Deepfakes can make epic memes or put Nicholas Cage in every movie, but they can also undermine elections. As threats of election interference mount, two teams of AI researchers have recently introduced novel approaches to identifying deepfakes by watching for evidence of heartbeats.
Existing deepfake detection models focus on traditional media forensics methods, like tracking unnatural eyelid movements or distortions at the edge of the face. The first study for detection of unique GAN fingerprints was introduced in 2018. But photoplethysmography (PPG) translates visual cues such as how blood flow causes slight changes in skin color into a human heartbeat. Remote PPG applications are being explored in areas like health care, but PPG is also being used to identify deepfakes because generative models are not currently known to be able to mimic human blood movements.