Efficient Privacy-Preserving Cube-Data Aggregation Scheme for Smart Grids

Efficient power management in smart grids requires obtaining power consumption data from each resident. However, data concerning user's electricity consumption might reveal sensitive information, such as living habits and lifestyles. In order to solve this problem, this paper proposes a privacy-preserving cube-data aggregation scheme for electricity consumption. In our scheme, a data item is described as a multi-dimensional data structure (l-dimensional), and users form and live in multiple residential areas (m areas, and at most n users in each area). Based on Horner's Rule, for each user, we construct a user-level polynomial to store dimensional values in a single data space by using the first Horner parameter. After embedding the second Horner parameter into the polynomial, the polynomial is hidden by using Paillier cryptosystem. By aggregating data from m areas, we hide the area-level polynomial into the final output. Moreover, we propose a batch verification scheme in multi-dimensional data to reduce authentication cost. Finally, our analysis shows that the proposed scheme is efficient in terms of computation and communication costs, suitable for massive user groups, and supports the flexible and rapid growth of residential scales in smart grids.

I. Introduction

Smart grid is considered as one of the most important trends in next-generation power grids, which integrates the traditional power grid system with advanced information and communication technology [1]–[4]. A reliable, secure, flexible, and manageable information and communication network is the backbone of smart grids [5]. To support various network functions, many intelligent electronic devices, such as intelligent terminals and smart meters, have been deployed and used in smart grid systems [6]. Due to the installation of smart meters at user side, two-way communication (which can implement request and response) is established, and demand response is possible [7]. However, attackers can eavesdrop on the communication channel between user and control center, and identify the user’s electricity demand [8]. They can then track the user’s living habits or lifestyle, which are private information of the residents [9], [10]. Therefore, privacy protection is a very important issue during deployment of smart grids.