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Quantifying Location Privacy [Test of Time Award IEEE S&P 21]

6 October 2021 @ 3:00 pm - 4:00 pm

We view location privacy as a statistical inference problem: The adversary makes noisy observations of the user’s location and then tries to infer the actual location. The privacy metric is then the attacker’s inference error. Modeling privacy in this way helps clarify and quantify assumptions about the adversary’s background knowledge, and it helps compare various protection mechanisms. This talk will present this approach, which was published at Oakland 2011 and received the Test of Time Award at Oakland 2021, and it will explore subsequent results in this area.

Zoom meeting: https://newcastleuniversity.zoom.us/j/85363650408?pwd=V2FHOFFGWW5VNnlpYXhhbHM5SFBkdz09

Meeting ID: 853 6365 0408
Passcode: 686689

Youtube live streaming: https://youtu.be/0uKDzeyUOOE

Youtube VoD


6 October 2021
3:00 pm - 4:00 pm


George Theodorakopoulos (Cardiff University)

George Theodorakopoulos received the Diploma degree from the National Technical University of Athens, Greece, in 2002, and the M.S. and Ph.D. degrees from the University of Maryland, College Park, MD, USA, in 2004 and 2007, all in electrical and computer engineering. He is a Senior Lecturer at the School of Computer Science and Informatics, Cardiff University, which he joined in 2012. From 2007 to 2011, he was a Senior Researcher at the Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland. He is a coauthor (with John Baras) of the book Path Problems in Networks (Morgan & Claypool, 2010). He received the Best Paper award at the ACM Workshop on Wireless Security, October 2004, for "Trust evaluation in ad-hoc networks" and the 2007 IEEE ComSoc Leonard Abraham prize for "On trust models and trust evaluation metrics for ad hoc networks." He coauthored "Quantifying Location Privacy," which was runner-up for the 2012 PET Award (Award for Outstanding Research in Privacy Enhancing Technologies) and received the Test of Time Award at the 2021 IEEE Symposium on Security and Privacy.

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