Private computation of spatial and temporal power consumption with smart meters

Abstract

Smart metering of utility consumption is rapidly becoming reality for multitudes of people and households. It promises real-time measurement and adjustment of power demand which is expected to result in lower overall energy use and better load balancing. On the other hand, finely granular measurements reported by smart meters can lead to starkly increased exposure of sensitive information, including all kinds of personal attributes and activities. Reconciling smart metering's benefits with privacy concerns is a major challenge. In this paper we explore some simple and relatively efficient cryptographic privacy techniques that allow spatial (group-wide) aggregation of smart meter measurements. We also consider temporal aggregation of multiple measurements for a single smart meter. While our work is certainly not the first to tackle this topic, we believe that proposed techniques are appealing due to their simplicity, few assumptions and peer-based nature, i.e., no need for any on-line aggregators or trusted third parties. © 2012 Springer-Verlag.