EFMDA: Efficient Fault-Tolerant Multidimensional Data Aggregation with Dual Privacy Protection in Smart Grids

Secure data aggregation is a powerful strategy for ensuring both data availability and privacy protection in smart grids. However, existing methods face two significant challenges: first, the substantial increase in communication and computation costs caused by malfunctioning smart meter; second, the risk of identity privacy leakage. To address these issues, we propose an efficient, fault-tolerant, and dual privacy-preserving data aggregation scheme. Our scheme effectively eliminates reliance on a trusted authority (TA) by leveraging an enhanced Paillier cryptosystem and a dual-secret sharing mechanism while ensuring robust fault tolerance. Additionally, it incorporates a pseudonym mechanism to safeguard user identity privacy. To meet the statistical requirements of modern smart grids, the scheme extends support for multidimensional data aggregation. Security analysis confirms that the proposed scheme provides dual privacy protection, ensures semantic security, and resists collusion attacks among participants. Furthermore, performance evaluations demonstrate that the proposed scheme maintains low communication and computation costs. Specifically, in fault-tolerant aggregation scenarios, its computation costs remain significantly lower than that of existing schemes, highlighting its efficiency. These results affirm the scheme’s practicality for smart grid applications.