A Privacy-Aware Data Aggregation Scheme for Smart Grid Based on Elliptic Curve Cryptography With Provable Security Against Internal Attacks

In smart grids (SGs), smart meters (SMs) are usually deployed to collect and transmit customers' electricity consumption data in real-time to the control center. Due to the open nature of the SG communication, several privacy-preserving data aggregation schemes have been proposed to protect the privacy of customers. However, most of these schemes cannot protect against internal attackers and they are not efficient, since SMs are constrained in processing, memory, and computing capabilities. To address these problems, the authors propose a privacy-aware lightweight data aggregation scheme against internal attackers based on Elliptic Curve Cryptography (ECC). The scheme satisfies all the security requirements of SG, and supports conditional traceability, strong anonymity and autonomy. The authors demonstrate that the proposed scheme provides confidentiality based on the Computational Diffie-Hellman (CDH) assumption and unforgeability in the security model based on the intractability of the Discrete Logarithm (DL) problem. Extensive performance analysis shows that the proposed scheme is very efficient.