Rigorous Systems Research Group (RSRG) Seminar

As many cyber-physical systems start to rely on collecting user data for more efficient operation, privacy has emerged as a concern among participating users. In this talk, I will discuss two frameworks that formalize the notion of privacy (differential privacy and information-theoretic privacy) from a unified point of view based on detection theory. I will demonstrate the applications of the two frameworks in energy systems through two case studies. (i) Private distributed charging of electric vehicles: It has been shown that the (non-private) distributed charging problem can be solved using distributed gradient descent. However, the messages exchanged between the center mediator and users may be exploited to breach the privacy of users. We show that differential privacy can be preserved by introducing additive noise to the gradients. We also quantify the trade-off between the level of privacy and the loss of utility using tools from optimization theory. (ii) Private smart metering with internal energy storage: We propose a new information-theoretic metric of privacy in order to handle the privacy of events (e.g., energy usage within any given time slot). The new metric is used to analyze the privacy of a smart metering system that uses internal energy storage as a buffer to hide distinctive energy usage patterns. The results quantify how the amount of energy storage helps improve the level of privacy.