Visible to the public SBE TWC: Small: Collaborative: Pocket Security - Smartphone Cybercrime in the WildConflict Detection Enabled

Project Details

Lead PI

Performance Period

Sep 15, 2016 - Aug 31, 2018


Fraunhofer Center for Experimental Software Engineering

Award Number

Most of the world's internet access occurs through mobile devices such as smart phones and tablets. While these devices are convenient, they also enable crimes that intersect the physical world and cyberspace. For example, a thief who steals a smartphone can gain access to a person?s sensitive email, or someone using a banking app on the train may reveal account numbers to someone looking over her shoulder. This research will study how, when, and where people use smartphones and the relationship between these usage patterns and the likelihood of being a victim of cybercrime. This research is the first step to a better scientific understanding how the physical world surrounding smartphone use enables cybercrime. Tired users may be less cautious in browsing to unsafe websites, or distracted users may miss a critical pop-up that a virus has been detected. Once these unsafe patterns of behavior are identified, new techniques, tools, and training can be developed to help prevent smartphone users from becoming victims of cybercrime.

This research expands existing theories of victimization in the domain of mobile devices, where both the criminal activity and the victimization occur online but may be affected by the offline environment. This research collects sensor data from the smartphones of 160 volunteers, such as GPS location, call frequency, and app usage. The smartphone sensor data is combined with questionnaires, demographic data from the U.S. Census, and neighborhood condition data from Google Street view. This research also provides a baseline of smartphone security threats stemming from behavioral and social factors, and applies new methods for social science research using mobile sensor data to unobtrusively observe the daily activities of subjects. Finally, this research adds to the body of knowledge on the fundamental limitations of sensor-based activity and context inferences, provides a unique corpus of smartphone sensor data that is freely available to the scientific community, and a set of open source tools for collecting and analyzing the data.