A recent study led by Carnegie Mellon professor Alessandro Acquisti used facial recognition software and Facebook information to figure out the partial Social Security numbers of some of the social network's users, the Wall Street Journal reports.
Acquisti used PittPatt software to determine the identities of random Facebook users, according to TechEye. Using this information, researchers were able to determine correct identity verification of 30 percent of those photographed. In addition, by using basic personal information posted on Facebook - such as birthplace and date of birth - Acquisti was able to predict the first five Social Security digits of 27 percent of the users studied. "Advances in the accuracy of facial recognition software are rapidly outpacing public awareness on internet privacy," Maria Fort, spokeswoman for privacy watchdog group Big Brother Watch, told the news source. "The increasing ease with which people can match the image of an individual to a Facebook profile ... means that anyone with the right technology has access to your most personal information." Acquisti was even able to construct a smartphone app that, using the face recognition technology, could correctly identify anonymous people on the street with a simple snapshot. The product will not be made available to the public.