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Speaker
Dr. John Krumm
Abstract
We generally give away our personal for free on the web. While technologies like differential privacy can protect our aggregated data, the holders of our data can still use it to make individual inferences about us that might be alarming. This talk will demonstrate some of these inferences for location data (GPS tracks) and for more general personal data as a first step to understanding and reducing the privacy risks. This leads to a study to see if people become more concerned about the privacy of their personal data if they know what could be inferred from it. Finally, I’ll discuss how we can compute a specific price for individual location points so people could sell their location data rather than give it away.
Biography
John Krumm graduated from the School of Computer Science at Carnegie Mellon University in 1993 with a PhD in robotics and a thesis on texture analysis in images. He worked at the Robotics Center of Sandia National Laboratories in Albuquerque, New Mexico for the next four years. His main projects there were computer vision for object recognition for use in robots and vehicles. He was at Microsoft Research in Redmond, Washington, USA for 25 years, starting in 1997. His research focuses on understanding peoples' location and personal data privacy. In 2017 he received a 10-year impact award for a paper on location privacy from the ACM UbiComp conference, and another from the same conference in 2021. He received the best paper award at the ACM SIGSPATIAL conference in 2022 and at the Mobile Data Management conference in the same year. His h-index on Google Scholar is 74. He is an inventor on 82 U.S. patents. Dr. Krumm was a PC chair for UbiComp 2007, ACM SIGSPATIAL 2013, and ACM SIGSPATIAL 2014. He is a past coeditor in chief of the Journal of Location Based Services. He currently serves as an associate editor for ACM Transactions on Spatial Algorithms and Systems and on the editorial board of IEEE Pervasive Computing Magazine. He is on the executive committee of ACM SIGSPATIAL and part of the Science Advisory Committee of the Geospatial Science and Human Security Division at Oak Ridge National Laboratory.
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