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Partial similarities between fingerprints are common enough to make fingerprint-based security systems in mobile phones and other electronic devices unreliable. This was discovered by researchers at the New York University (NYU) Tandon School of Engineering and Michigan State University College of Engineering,
According to homelandsecuritynewswire.com, the vulnerability lies in the fact that these systems’ sensors don’t capture a user’s full fingerprint. Instead, they scan and store partial fingerprints, and many phones allow users to enroll several different fingers in their authentication system. Identity is confirmed when a user’s fingerprint matches any one of the saved partial prints. The researchers hypothesized that there could be enough similarities among different people’s partial prints that one could create a “MasterPrint.”
Nasir Memon, a professor of computer science and engineering at NYU Tandon and the research team leader, explained that the MasterPrint concept bears similarities to a hacker who attempts to crack a PIN-based system using a commonly adopted password such as 1234. “About 4 percent of the time, the password 1234 will be correct, which is a relatively high probability when you’re just guessing,” he explained. The research team set out to see if they could find a MasterPrint that could reveal a similar level of vulnerability. Indeed, they found that certain attributes in human fingerprint patterns were common enough to raise security concerns.
Memon and his colleagues, NYU Postdoctoral Aditi Roy and Michigan State University Professor of Computer Science and Engineering Arun Ross, undertook their analysis using 8,200 partial fingerprints. Using commercial fingerprint verification software, they found an average of 92 potential MasterPrints for every randomly sampled batch of 800 partial prints (they defined a MasterPrint as one that matches at least 4 percent of the other prints in the randomly sampled batch).
They found, however, just one full-fingerprint MasterPrint in a sample of 800 full prints. “Not surprisingly, there’s a much greater chance of falsely matching a partial print than a full one, and most devices rely only on partials for identification,” said Memon.
The team analyzed the attributes of MasterPrints culled from real fingerprint images and designed an algorithm for creating synthetic partial MasterPrints. Experiments showed that synthetic partial prints have an even wider matching potential, making them more likely to fool biometric security systems than real partial fingerprints. With their digitally simulated MasterPrints, the team reported successfully matching between 26 and 65 percent of users, depending on how many partial fingerprint impressions were stored for each user and assuming a maximum number of five attempts per authentication. The more partial fingerprints a given smartphone stores for each user, the more vulnerable it is.
The high matching capability of MasterPrints points to the challenges of designing trustworthy fingerprint-based authentication systems and reinforces the need for multi-factor authentication schemes. “As fingerprint sensors become smaller in size, it is imperative for the resolution of the sensors to be significantly improved in order for them to capture additional fingerprint features,” Ross said. “If resolution is not improved, the distinctiveness of a user’s fingerprint will be inevitably compromised”.