E-LPDAE: An Edge-Assisted Lightweight Power Data Aggregation and Encryption Scheme. (18th April 2022)

• Record Type: Journal Article
• Authors: Wu, Junhua; Xu, Zhuqing; Li, Guangshun; Fan, Cang; Jin, Zhenyu; Zheng, Yuanwang
• Other Names: Xiong Jinbo Academic Editor.
• Is Part Of: Security and communication networks. Volume 2022(2022)
• Publication Date: 2022-04-18
• Subjects: Computer networks -- Security measures -- Periodicals; Computer security -- Periodicals; Cryptography -- Periodicals; 005.805
• DOI: 10.1155/2022/6218094
• Languages: English
• ISSNs: 1939-0114

Abstract

Abstract : In smart grid systems, electric utilities require real-time access to customer electricity data; however, these data might reveal users' private information, presenting opportunities for edge computing to encrypt the information while also posing new challenges. In this paper, we propose an Edge-assisted Lightweight Power Data Aggregation Encryption (E-LPDAE) scheme for secure communication in a smart grid. First, in the edge privacy aggregation model, the data of smart meters are rationally divided and stored in a distributed manner using simulated annealing region division, and the edge servers of trusted organizations perform key one-time settings. The model encrypts the data using Paillier homomorphic encryption. It then runs a virtual name-based verification algorithm to achieve identity anonymization and verifiability of the encrypted data. The experimental results indicate that the E-LPDAE scheme reduces overall system power consumption and has significantly lower computation and communication overhead than existing aggregation schemes.