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Understanding Human Behaviors at Large Scales through Mobile Devices

Researchers: Jason Hong, Norman Sadeh, Justin Cranshaw, Eran Toch

Research Area: Mobility | Privacy Protection | Security of Cyber-Physical Systems

Abstract

Scope: Today’s mobile devices come with an incredible array of capabilities. A commodity smart phone can sense location, sound, proximity, and motion. These devices also have access to call logs, SMS logs, pictures taken, and email. These new capabilities offer us the opportunity to analyze real-world social networks and human behaviors at unprecedented fidelity and scale, in ways that previously were simply not possible. As such, mobile devices can be thought of as a new scientific tool for computational social science of real-world interactions, activities, and behaviors. We are gathering large quantities of sensor data and communication data from volunteers, and using this data to build better models of our real-world social networks. We are also using this data to understand issues of privacy.

Outcomes: Since phish are generated from toolkits, multiple copies of a site are likely to appear. As such, we have implemented a way of clustering similar phish together to improve people’s ability to identify phish, as well as to improve efficiency. We are currently evaluating the effectiveness of these techniques.