The widespread deployment of smart meters for the modernization of the electricity distribution network has been associated with privacy concerns due to the potentially large number of measurements that reflect the consumers’ behavior. At the same time, how to extract important knowledge from the potentially large of measurements — these measurements are spilt among various parties, has already became a hot topic in the field of data mining. In this paper, we present protocols that can be used to compute meter measurements over defined sets of meters without revealing any additional about the individual meter readings, and address secure mining of association rules. Thus, most of the benefits of the smart grid can be achieved without revealing individual data.
