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A hack that fools Face Recognition AI into false identification


Face recognition AI is increasingly being used at Airports and at other security outlets, especially during a pandemic to heed to proper security measures of identifying people while maintaining social distancing but a recent discovery by McAfee, a cybersecurity firm has proved that these Face Recognition systems are not all that perfect.

Researchers at McAfee tested a face recognition system similar to the ones used at Airports for passport verification- they fed the system an image created by machine learning that looks like one person but is recognized as someone else by the face recognition software. This could allow someone to board a flight (who is on the no-flight list) as someone else who has the booking.

“If we go in front of a live camera that is using facial recognition to identify and interpret who they're looking at and compare that to a passport photo, we can realistically and repeatedly cause that kind of targeted misclassification,” said the researcher, Steve Povolny.

To trick the face recognition algorithm the researchers at McAfee used CycleGAN, which is an image translation algorithm that could transform your picture to make it look like something painted by Monet or make a summer picture look like a winter one.

The team used 1,500 photos of the project leads to be transformed by CycleGAN and after hundred of tries, CycleGAN created an image that the face recognition recognized as someone else instead of whom the human eye perceived.

But there are two concerns with the study- first, that the researchers had a similar face recognition system as they do at the airport security but not the same.“I think for an attacker that is going to be the hardest part to overcome, where [they] don’t have access to the target system” said Povolny. Second, CycleGAN takes time to create such an image and the software requires a high-end system to work functionally.

 The researchers aimed at the study to point out the vulnerability of Face recognition systems and the dangers of relying solely on these checks.

"AI and facial recognition are incredibly powerful tools to assist in the pipeline of identifying and authorizing people,” Povolny says. “But when you just take them and blindly replace an existing system that relies entirely on a human without having some kind of a secondary check, then you all of a sudden have introduced maybe a greater weakness than you had before.”

San Francisco to ban facial recognition







Law makers in San Francisco have voted to ban the use of face recognition technology by city agencies, including the police department while provoking worries over privacy.

The new bill  Stop Secret Surveillance Ordinance, was introduced by San Francisco Supervisor Aaron Peskin. The ordinance states that any plans to buy any kind of new surveillance technology must now be approved by city administrators.

"With this vote, San Francisco has declared that face surveillance technology is incompatible with a healthy democracy and that residents deserve a voice in decisions about high-tech surveillance," said Matt Cagle from the American Civil Liberties Union in Northern California.

"We applaud the city for listening to the community, and leading the way forward with this crucial legislation. Other cities should take note and set up similar safeguards to protect people's safety and civil rights."

Face recognition technology uses an algorithm that scans a person’s face and then matches it with pre saved database. This technology is now commonly used by smartphones, laptops, and other digital device companies. 

San Francisco is the first US city to ban the face recognition.