So
you think you can secure
your mobile phone with a fingerprint?
NYU Tandon School of
Engineering
No two people are
believed to have identical fingerprints, but researchers at the New York
University Tandon School of Engineering and Michigan State University College
of Engineering have found that partial similarities between prints are common
enough that the fingerprint-based security systems used in mobile phones and
other electronic devices can be more vulnerable than previously thought.
The vulnerability lies
in the fact that fingerprint-based authentication systems feature small sensors
that do not 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."
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 some similarity 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," said Memon. 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 Tandon Postdoctoral Fellow 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.)
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 then built
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.
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.
Roy emphasized that
their work was done in a simulated environment. She noted, however, that
improvements in creating synthetic prints and techniques for transferring
digital MasterPrints to physical artifacts in order to spoof a device pose
significant security concerns.
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. She said this work may inform future designs.
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. She said this work may inform future designs.
"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. The
empirical analysis conducted in this research clearly substantiates this."
Memon noted that the
results of the team's research are based on minutiae-based matching, which any
particular vendor may or may not use. Nevertheless, as long as partial
fingerprints are used for unlocking devices and multiple partial impressions
per finger are stored, the probability of finding MasterPrints increases
significantly, he said.
"NSF's
investments in cybersecurity research build the foundational knowledge base
needed to protect us in cyberspace," said Nina Amla, program director in
the Division of Computing and Communication Foundations at the National Science
Foundation.
"Much as other NSF-funded research has helped identify vulnerabilities in everyday technologies, such as cars or medical devices, investigating the vulnerabilities of fingerprint-based authentication systems informs continuous advancements in security, ensuring more reliable protection for users."
"Much as other NSF-funded research has helped identify vulnerabilities in everyday technologies, such as cars or medical devices, investigating the vulnerabilities of fingerprint-based authentication systems informs continuous advancements in security, ensuring more reliable protection for users."