An Efficient Data Aggregation Scheme for Privacy-Friendly Dynamic Pricing-Based Billing and Demand-Response Management in Smart Grids

Smart grids take advantage of information and communication technologies to achieve energy efficiency, automation, and reliability. These systems allow two-way communications and power flow between the grid and consumers. However, these bidirectional communications introduce several security and privacy threats to consumers. One of the open challenges in this context is user privacy when smart meters (SMs) are used to capture fine-grained energy usage information. Although considerable research has been carried out in this direction, most of the existing solutions invariably introduce computational complexity and overhead, which makes them infeasible for resource constrained SMs. In this paper, we propose a privacy-friendly and efficient data aggregation scheme for dynamic pricing-based billing and demand-response management in smart grids. To the best of our knowledge, this is thefirst paperto address privacy in the context of billing under dynamic electricity pricing. Security and performance analyses show that the proposed scheme offers better privacy protection for electric meter reading aggregation and computational efficiency, as compared to existing schemes.