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[PAST EVENT] Colloquium: Mobile Sensing and Behavior Modeling: Implications on Security
March 1, 2013
3pm
Today's smart phones come equipped with a rich range of sensors including GPS, accelerometers, WiFi, Bluetooth, NFC, microphone, etc. Combined, this contextual information can tell us a great deal about a user's current activity: what is the user doing now at which location and for how long. When logged, this data can provide important information about the user's behavior patterns. Through statistical behavior modeling over the sensor time series, we demonstrate how mobile sensing can be used to estimate the "behavior metric" of the user for passive authentication and anomaly detection.
Bio: Dr. Joy Ying Zhang is an assistant research professor in the Mobility Research Center at Carnegie Mellon University, Silicon Valley. He received his Ph.D. from Language Technologies Institute of Carnegie Mellon University. Most of his research centers around applying statistical learning on natural language processing problems and behavior modeling problems. His current research interests lie in developing the CMU MobiSens mobile App and the CMU lifelogging system for real-world behavior modeling using structured learning.
Bio: Dr. Joy Ying Zhang is an assistant research professor in the Mobility Research Center at Carnegie Mellon University, Silicon Valley. He received his Ph.D. from Language Technologies Institute of Carnegie Mellon University. Most of his research centers around applying statistical learning on natural language processing problems and behavior modeling problems. His current research interests lie in developing the CMU MobiSens mobile App and the CMU lifelogging system for real-world behavior modeling using structured learning.
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Department of Computer Science