NLSP: A novel lattice‐based secure primitive for privacy‐preserving smart grid communications

• Published in: Concurrency and computation Vol. 35; no. 19
• Main Authors: Bao, HaiYong, Xu, Zheng, Hong, HaiBo, Kong, QingLei, Qian, HaiFeng
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 30.08.2023
• Subjects: Algorithms; Communication; Computing costs; Cybersecurity; Data communication; Data encryption; Data management; data packing; Data structures; differential privacy; Efficiency; Encryption; homomorphic encryption; Homomorphisms; lattice‐based cryptography; multi‐dimension; Performance evaluation; Privacy; Smart grid; Topology
• ISSN: 1532-0626; 1532-0634
• DOI: 10.1002/cpe.7406

Summary As the new generation of power scheme, smart grid is proposed to overcome the shortcomings of traditional systems, such as low efficiency and reliability. In this article, a novel lattice‐based secure primitive for privacy‐preserving smart grid communications is proposed, which has the remarkable characteristics, such as scalable multi‐dimensional fine‐grained power data structure and differential privacy security. First, combining with the lattice‐based data encryption technology, while effectively resisting quantum attacks, the method of simultaneous processing of multi‐dimensional data is innovated. Second, through combining the additive homomorphism of the lattice‐based cryptosystem and the Chinese remainder theorem, the data aggregation mechanism that can directly perform homomorphic operations on compressed ciphertext is constructed. Thanks to the above innovative design ideas, the proposed scheme not only significantly improves the efficiency of data communication and processing, greatly reduces the computational cost of the intermediate entity, but also realizes the data confidentiality and information privacy. Finally, observing the decentralized topology of communication nodes in the typical cyber‐physical system of smart grid, the localized differential privacy technology is leveraged to optimize and balance the utility, security, and efficiency of differential privacy. Extensive performance evaluations are conducted to illustrate that the proposed scheme outperforms the state‐of‐the‐art similar schemes in terms of computation complexity and communication cost.