Lattice-Based Homomorphic Encryption For Privacy-Preserving Smart Meter Data Analytics.

This article focuses on a privacy-preserving architecture for smart meter data collection and analysis in smart grids using lattice-based homomorphic encryption (HE), specifically the CKKS cryptosystem. The proposed method enables encrypted data aggregation and computation—such as billing, variance calculation, and nonlinear support vector machine (SVM) classification—without revealing individual user data, addressing privacy concerns inherent in fine-grained smart meter readings. The authors introduce a distributed key management system based on secure multi-party computation (MPC) to avoid centralized trusted authorities and single points of failure. Performance evaluations demonstrate that the CKKS-based approach offers greater computational efficiency and flexibility compared to classical HE schemes like Paillier and Boneh–Goh–Nissim (BGN), while communication overhead and latency are analyzed for different data reporting frequencies and multiplicative depths.