A Lightweight and Privacy-Preserving Data Aggregation for Dynamic Pricing-based Billing in Smart Grids

Abstract

Smart grids are expected to enhance the efficiency of current power grids by using advanced digital information and communication technology. However, as the power grid is extended to network of networks, it not only becomes smarter, but also more vulnerable to several security and privacy threats. One of the major concerns with the scale of data collection in smart grids, and in particular smart meters, is that of privacy. While several solutions have been introduced to address this issue, they are computationally complex and introduce large overheads, making them infeasible for resource constrained smart meters. In addition, given the large scale of most smart grids, the computational burden at the aggregator of smart meter data is also a challenging issue. In this article, we propose a lightweight and privacy-preserving data aggregation (LPDA) scheme for dynamic electricity pricing based billing for smart grids using the concept of lightweight single-pass authenticated encryption (AE). Security and performance analyses show that our proposed scheme offers better privacy protection for electricity meter reading aggregation and computational efficiency, as compared to the existing solutions.