New Method Can Catch Smartphone Thieves In 14 Seconds

New research from Ben-Gurion University of the Negev shows promise in quickly identifying smartphone hackers.

Steve Zurier, Contributing Writer, Dark Reading

February 7, 2017

1 Min Read
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Researchers at Ben-Gurion University of the Negev claim they have developed a technique based on sequences of gestures that identifies a smartphone thief in under 14 seconds.

"It can even be faster, a matter of seconds, depending on how many gestures there are," says BGU researcher Liron Ben Kimon.

According to Ben Kimon, the researchers culled information from 20 users over a two-week period last fall to develop a model that shows unauthorized users can be identified in under 14 seconds with less than 35 screen actions. She says on average, a user touches a smartphone screen 35 times in 13.8 seconds.

The verification model extracts information from a smartphone’s sensors to identify frequency, pressure and speed of touch combined with the application used. The program also computes 30 seconds of recent history, such as which screens a user touched, the buttons he or she pressed, and how much electricity was used.

"A thief will almost certainly touch the screen more than 35 times to steal information because he is not familiar with an owner’s phone settings and apps," Ben Kimon said in an announcement of the research today. "The phone can learn the typical touch and sequence pattern and lock out an unauthorized user to prevent data theft or someone you don’t want looking at your messages."

Ben Kimon underscores that this is still in the research stages and no commercial applications have been formally discussed. Kimon says it would be possible for the system to send an alert to an organization’s incident response system.

About the Author

Steve Zurier

Contributing Writer, Dark Reading

Steve Zurier has more than 30 years of journalism and publishing experience and has covered networking, security, and IT as a writer and editor since 1992. Steve is based in Columbia, Md.

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