IEEE SPS UK & Ireland Distinguished Lecturer Seminar at UCD: Prof. Urbashi Mitra, Exploiting Statistical Hardness for Increased Privacy in Wireless Systems
The IEEE Signal Processing Society UK & Ireland Chapter is pleased to welcome Professor Urbashi Mitra to the University College Dublin for a Distinguished Lecturer seminar.
Title: Exploiting Statistical Hardness for Increased Privacy in Wireless Systems
Abstract: Securing signals from unintended eavesdroppers has become an increasingly important problem with the emergence of the Internet-of-Things. Herein, we examine learning problems in signal processing that are inherently hard without key side information. In particular, we exploit necessary resolution limits for classical compressed sensing problems. To limit an eavesdropper's capabilities, we create an environment for the eavesdropper wherein the appropriate compressed sensing algorithm would probably fail. The intended receiver overcomes this ill-posed problem by leveraging secret side information shared between the intended transmitter and receiver. Two scenarios are considered: one for communication over a wireless channel where a novel block-sparsity based signaling strategy is employed and one for localization where novel structured noise is introduced to degrade the form of the eavesdropper’s channel. In the latter scenario, the transmitter designs a beamformer that introduces spurious paths, or spoofs the line-of-sight path, in the channel without having access to the channel state information. In both private communication and private localization, the amount of secret information that must be shared is very modest. Theoretical guarantees can be provided for both cases. Proposed algorithms are validated via numerical results. Finally, the idea of statistical hardness is applied to a distributed learning (federated) problem and shown to be effective in providing model privacy against eavesdroppers.
Date and Time
Location
Hosts
Registration
-
Add Event to Calendar
- Room 204, UCD Engineering & Materials Science Centre
- Dublin, Dublin
- Ireland 8Q4J+HJ
Speakers
Urbashi Mitra
Exploiting Statistical Hardness for Increased Privacy in Wireless Systems
Biography:
Urbashi Mitra received the B.S. and the M.S. degrees from the University of California at Berkeley and her Ph.D. from Princeton University. She began her academic career at Ohio State University. Dr. Mitra is currently the Gordon S. Marshall Professor in Engineering at the University of Southern California with appointments in Electrical Engineering and Computer Science. Dr. Mitra is a Fellow of the IEEE, a foreign member of the Academia Europaea and a member of the USC chapter of Phi Kappa Phi. She was the inaugural Editor-in-Chief for the IEEE Transactions on Molecular, Biological and Multi-scale Communications as well as multiple Associate editorships for IEEE transactions. She is active in service for the following IEEE societies: Signal Processing, Communications and Information Theory. She is the recipient of: the 2025 Princeton ECE Department Distinguished Graduate Alumni Award, the 2024 IEEE Information Theory Society Aaron D. Wyner Distinguished Service Award, the 2021 USC Viterbi School of Engineering Senior Research Award, the 2017 IEEE Communications Society Women in Communications Engineering Technical Achievement Award, a 2016 UK Royal Academy of Engineering Distinguished Visiting Professorship, a 2016 US Fulbright Scholar Award, a 2016-2017 UK Leverhulme Trust Visiting Professorship, IEEE Communications Society (2015-2016) and Signal Processing Society (2024-2025) Distinguished Lectureships, 2012 Globecom Signal Processing for Communications Symposium Best Paper Award, 2012 US National Academy of Engineering Lillian Gilbreth Lectureship, the 2009 DCOSS Applications & Systems Best Paper Award, 2002 Texas Instruments Visiting Professor, 2001 Okawa Foundation Award, 2000 OSU College of Engineering Lumley Award for Research, 1997 OSU College of Engineering MacQuigg Award for Teaching, and a 1996 National Science Foundation CAREER Award. Dr. Mitra has held visiting appointments at: King’s College, London, Imperial College, the Delft University of Technology, Stanford University, Rice University, and the Eurecom Institute. Her research interests are in: model-based machine learning, wireless communications, communication and sensor networks, biological communication systems, detection and estimation and the interface of communication, sensing and control.
Address:United Kingdom