Elastic Pathing - HCI work on MIT Technology Review

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Prof. Lindqvist's work appeared in MIT Technology Review
http://www.technologyreview.com/view/523346/how-to-track-vehicles-using-speed-data-alone/

The full article can be found at   http://arxiv.org/abs/1401.0052

Prof. Janne Lindqvist, a recently appointed assistant professor of electrical and computer engineering, member of WINLAB and director of the Human-Computer Interaction Laboratory, led a team to show how just your driving speed can be used to track where you drive.   This work, "Elastic Pathing: Your Speed is Enough to Track You" is part of a NSF-funded project for which Prof. Janne Lindqvist is the sole Principal Investigator.  

Prof. Janne Lindqvist's team included ECE PhD students Berhard Firner, Yulong Yang, and recently graduated Master's student Shridatt Sugrim.


The motivation for the project was that today people increasingly have the opportunity to opt-in to "usage-based" automotive insurance programs for reducing insurance premiums. In these programs, participants install devices in their vehicles that monitor their driving behavior, which raises some privacy concerns. Some devices collect fine-grained speed data to monitor driving habits.

Companies that use these devices claim that their approach is privacy-preserving because speedometer measurements do not have physical locations.

However, in their work the team showed that with knowledge of the user's home location, as the insurance companies have, speed data is sufficient to discover driving routes and destinations when trip data is collected over a period of weeks. To demonstrate the real-world applicability of their approach the team applied their algorithm, elastic pathing, to data collected over hundreds of driving trips occurring over several months. With this data and their approach, they were able to predict trip destinations to within 250 meters of ground truth in 10% of the traces and within 500 meters in 20% of the traces. This result, combined with the amount of speed data that is being collected by insurance companies, constitutes a substantial breach of privacy because a person's regular driving pattern can be deduced with repeated examples of the same paths with just a few weeks of monitoring.

Please contact Prof. Janne Lindqvist at   janne @ winlab.rutgers.edu for any further questions.