A study on users' smartphone and app usage has been published in the journal Psychological Science.
Researchers from Lancaster University and the University of Bath in the United Kingdom analyzed 4,680 days worth of app usage data from 780 people's smartphones, creating models of their daily app usage patterns. They then tested whether the models could identify individuals based on only one day of anonymous smartphone usage activity.
"Our models, which were trained on only six days of app usage data per person, could identify the correct person from a day of anonymous data one third of the time," said Dr. Ellis from the University of Bath.
The models were able to generate a list of the most to least likely candidates for a given day of activity, in which the top ten most likely candidates contained the correct user 75% of the time. The researchers warn that software with access to standard activity logs could reasonably predict a user's identity, even when logged out, and without access to conversations or behaviors from within apps.
"In practical terms, a law enforcement investigation seeking to identify a criminal's new phone from knowledge of their historic phone use could reduce a candidate pool of approximately 1,000 phones to 10 phones, with a 25% risk of missing them," said Professor Taylor from Lancaster University.
"We found that people exhibited consistent patterns in their application usage behaviours on a day-to-day basis, such as using Facebook the most and the calculator app the least. In support of this, we also showed that two days of smartphone data from the same person exhibited greater similarity in app usage patterns than two days of data from different people," said Dr. Shaw from Lancaster University.
You can read more from the study here.
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