Facial recognition tech makes it easier to combine offline, online identities
Imagine walking down a street and having a total stranger being able to instantly pull up your name, date of birth, Social Security number, your last blog item and other data on their smart phone.
That could soon happen, said Alessandro Acquisti, associate professor of IT and public policy at Carnegie Mellon University's Heinz College.
In a presentation at the Black Hat conference here this week, Acquisti demonstrated how it's becoming easier for strangers to identify people and infer detailed information about them from their publicly available images on sites such as Facebook and LinkedIn.
The trend has "ominous implications for privacy," Acquisti said. "I'm here to raise awareness of what I feel is going to happen."
Acquisti detailed the results of a series of experiments he conducted in which he applied off-the-shelf facial recognition tools to publicly available Facebook profile images to uniquely identify individuals. In one of the experiments, Acquisti and his team of researchers attempted to glean the true identities of individuals who had posted their images under assumed names on an online dating site
First, they used a search engine and an API they developed to automatically extract about 275,000 publicly available profile images of Facebook members in a particular city.
They then did the same with publicly available images of individuals in the same city who had posted on the dating site. Acquisti used a facial recognition tool called Pittsburgh Pattern Recognition (PittPatt) developed at CMU to see whether he could find matches between the dating site images and the Facebook profile pictures.
In all, about 5,800 dating site members also had Facebook profiles. Of these, more than 4,900 were uniquely identified. The numbers are significant because a previous CMU survey showed that about 90% of Facebook members use their real name on their profiles, Acquisiti said. Though the dating site members had used assumed names to remain anonymous, their real identities were revealed just by matching them with their Facebook profiles.
In another experiment, Acquisti's team took webcam photos of nearly 100 students and tried to match those images with the pictures on each student's Facebook profile.
Students were asked to pose for three photos and then fill out a short survey. While the surveys were being filled out, the webcam images were run against PittPatt to see whether a match could be found on Facebook.
In that experiment, about 31% of the students were correctly matched with their Facebook profiles -- in about 3 seconds.