Project Leader: Farhad Farokhi
Collaborators: Henrik Sandberg (KTH Royal Institute of Technology, Sweden)
Sponsors: The University of Melbourne
Primary Contact: Farhad Farokhi (firstname.lastname@example.org)
Keywords: data privacy; information theory; optimisation; signal processing
Disciplines: Electrical & Electronic Engineering
For privacy protection, the responses to the queries are systematically corrupted with an additive random noise. Using the Cramer-Rao bound, we can relate the variance of any estimator of the private database entries to the inverse of the trace of the Fisher information matrix, motivating its use as a measure of privacy. We can compute the probability density that minimizes the trace of the Fisher information (as a proxy for maximising the measure of privacy) to find the optimal privacy-preserving policy. There is still much to do in this arena specially when dealing with dynamical systems at the heart of transportation systems and smart grids.
Further information: http://farokhi.xyz/2020/02/24/fisher-information-privacy/