You don't have to wear a Halloween mask to avoid being detected by facial recognition software: a dab of makeup will do the trick, according to a new study. Researchers at Ben-Gurion University in Beersheba, Israel, developed an artificial intelligence that shows users where to apply some foundation or rouge to fool face-recognition algorithms into thinking they're looking at a different person. The researchers tested their scheme against ArcFace, a machine-learning model that takes two facial images and determines the likelihood they're the same person. The team used 20 volunteers (10 men and 10 women) in a real-world environment using two cameras and a variety of lighting conditions and shooting angles. Participants wearing'adversarial makeup,' as recommended by the program, tricked the system 98.8 percent of the time.

Deepfakes, or AI-generated videos that take a person in an existing video and replace them with someone else's likeness, are multiplying at an accelerating rate. According to startup Deeptrace, the number of deepfakes on the web increased 330% from October 2019 to June 2020, reaching over 50,000 at their peak. That's troubling not only because these fakes might be used to sway opinion during an election or implicate a person in a crime, but because they've already been abused to generate pornographic material of actors and defraud a major energy producer. Open source tools make it possible for anyone with images of a victim to create a convincing deepfake, and a new study suggests that deepfake-generating techniques have reached the point where they can reliably fool commercial facial recognition services. In a paper published on the preprint server Arxiv.org,

Ubiquitous facial recognition is a serious threat to privacy. The idea that the photos we share are being collected by companies to train algorithms that are sold commercially is worrying. Anyone can buy these tools, snap a photo of a stranger, and find out who they are in seconds. But researchers have come up with a clever way to help combat this problem. The solution is a tool named Fawkes, and was created by scientists at the University of Chicago's Sand Lab.

Facial recognition is being widely embraced as a security tool -- law enforcement and corporations alike are rolling it out to keep tabs on who's accessing airports, stores, and smartphones. As it turns out, the technology is fallible. Researchers with the artificial-intelligence firm Kneron announced that they were able to fool some facial-recognition systems using a printed mask depicting a different person's face. The researchers, who tested systems across three continents, said they fooled payment tablets run by the Chinese companies Alipay and WeChat, as well as a system at a border checkpoint in China. In Amsterdam, a printed mask fooled facial recognition at a passport-control gate at Schiphol Airport, they said.

Facial recognition is being widely embraced as a security tool -- law enforcement and corporations alike are rolling it out to keep tabs on who's accessing airports, stores, and smartphone lock screens. As it turns out, the technology is fallible. Researchers with the AI firm Kneron were able to fool facial recognition systems at banks, border crossing checkpoints, and airports using a printed mask depicting a different person's face, they announced Thursday. Researchers tested facial recognition across three continents. They successfully fooled payment tablets run by Chinese companies Alipay and WeChat, as well as a border crossing checkpoint in China.