Differential privacy in control and network systems

Jorge Cortes, Geir E. Dullerud, Shuo Han, Jerome Le Ny, Sayan Mitra, George J. Pappas
2016 2016 IEEE 55th Conference on Decision and Control (CDC)  
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
more » ... nforcing differential privacy, a state-ofthe-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.
doi:10.1109/cdc.2016.7798915 dblp:conf/cdc/CortesDHNMP16 fatcat:ahcmnwkzjrb4nbt7uditlsxsb4