Differential privacy for real smart metering data

Abstract

The collection of detailed consumption data through smart metering has led to privacy concerns. Aggregating the consumption data over a number of smart meters can be used to strike a balance between functional and privacy requirements. A number of contributions have proposed the use of differential privacy in smart metering to perturb aggregates in order to provide a proven privacy property for end consumers. However, as differential privacy has originally been proposed for very large datasets, the applicability in real-world smart metering is not guaranteed. In this paper, the effect of differential privacy on real smart metering data is studied, especially with respect to balancing utility and privacy requirements. The main finding is that even after some improvements of the basic method the aggregation group size must be of the order of thousands of smart meters in order to have reasonable utility.