Security specialists from the University of North Carolina have revealed a spoofing method for facial recognition which uses digital 3-D facial models and photos in the public domain.Presented at the Usenix security conference earlier in August, the method involves creating a VR-style face, rendered in three dimensions, from publically available images, writes Wired.Because this gives the motion and depth pointers that many face recognition tools work from, the team was able to bypass the biometric security.To gather attach subjects, the team simply harvested images through picture research engines, experienced pics, and publicly offered assets on social networks like Facebook, LinkedIn, and Google+.In addition to building facial area types from on the net pics, the scientists also took indoor head pictures of each individual participant, rendered them for virtual fact, and tested these.To test the security systems, the researchers had the subjects program each one to detect their real faces. Then they showed 3-D renders of each subject to the systems to see if they would accept them.Researchers would try using texture data from a different photo, ensure each face render was altered so eyes appeared to look directly into the camera for authentication. The faces were also animated as needed for “liveness clues” like blinking, smiling, and raising eyebrows.The scientists said they were able to trick five applications in each case they tested. Using the public net pics, the scientists were ready to trick four of these with good results ranging from 55 percent up to 85 percent.Speaking to the magazine, biometrics expert Anil Jain said: “It is now well known that face biometrics are easy to spoof compared to other major biometric modalities, namely fingerprints and irises”. However, he added “While 3-D face models may visually look similar to the person's face that is being spoofed, they may not be of sufficiently high quality to get authenticated by a state of the art face matcher.”
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