Efficient privacy-preserving temporal and spacial data aggregation for smart grid communications

Smart grid is ever-increasingly adopted by nations and governments for its grand development with the underlying technologies of power management and information communications. The real-time electricity usage can be monitored and aggregated by the smart meters deployed in the household for further analysis, control, and pricing. However, the existing solutions mainly depend on Paillier's additive homomorphic encryptions taking high computational complexity, and the aggregation mainly focused on the time series data generated by one single user. In this paper, we propose an efficient privacy-preserving temporal and spacial data aggregation from one-way functions in smart grid communications, which also allows spacial data aggregation from multiple users. The proposed construction can guarantee the unconditional security of users' metering power data privacy from the community gateway and the operation center, and the Adaptive Chosen Ciphertext Attack (CCA2) security of the aggregation result that can only be accessed by the authorized operating center. Both temporal and spacial data aggregation only require computing the underlying one-way function once. The formal security proof and performance evaluations demonstrate the efficiency and the practicability of our scheme.