Jorge Cortés
Professor
Cymer Corporation Endowed Chair
Differential privacy in control and network systems
J. Cortés, G. E. Dullerud, S. Han, J. Le Ny, S. Mitra, G. J. Pappas
Proceedings of the IEEE Conference on Decision and
Control, Las Vegas, Nevada, USA, 2016, pp. 4252-4272
Abstract
As intelligent automation and large-scale distributed monitoring and
control systems become more widespread, concerns are growing about
the way these systems collect and make use of privacy-sensitive data
obtained from individuals. This tutorial paper gives a systems and
control perspective on the topic of privacy preserving data
analysis, with a particular emphasis on the processing of dynamic
data as well as data exchanged in networks. Specifically, we
consider mechanisms enforcing differential privacy, a
state-of-the-art definition of privacy initially introduced to
analyze large, static datasets, and whose guarantees hold against
adversaries with arbitrary side information. We discuss in
particular how to perform tasks such as signal estimation, consensus
and distributed optimization between multiple agents under
differential privacy constraints.
pdf
Mechanical and Aerospace Engineering,
University of California, San Diego
9500 Gilman Dr,
La Jolla, California, 92093-0411
Ph: 1-858-822-7930
Fax: 1-858-822-3107
cortes at ucsd.edu
Skype id:
jorgilliyo