Enabling Efficient and Privacy-Preserving Aggregation Communication and Function Query for Fog Computing-Based Smart Grid

Compared with the traditional grid, smart grid involves a lot of advanced technologies and applications. However, due to rapid development, it faces a challenge to balance privacy, security, efficiency, and functionality. In this paper, we build a fog computing-based smart grid model and then present an efficient and privacy-preserving scheme which supports aggregation communication and function query based on the proposed model. To the best of our knowledge, this is the first concrete solution focusing on aspects of aggregation communication and data availability (e.g., function query) simultaneously in smart grid. In doing so, we utilize geographically distributed massive fog nodes and a centralized cloud server to achieve low-latency communication and electricity data storage. Encrypted under a double trapdoor cryptosystem, the usage data can be efficiently aggregated by fog nodes. Which supports the service provider to dynamically control and distribute the electricity. With outsourcing the encrypted usage data to the cloud, our scheme allows the service provider to launch various function queries on encrypted usage data, which is necessary for its services (e.g., billing), while letting users to have control of their own data. Therefore, our scheme can be applied to more complex smart grid applications compared with other solutions. Security proofs and analyses show that our scheme guarantees data privacy, confidentiality, authentication, and integrity. Finally, we compare our scheme with related works in terms of functionalities and most importantly, implement the scheme in a simulation environment. Experimental results indicate that our scheme is efficient with low computation and communication overheads.