BPRM: Blockchain-Based Privacy Preserving and Robust Data Aggregation Supporting Multifunctionality for Fog-Assisted Smart Grid

作     者：Zhao, Chuankun Wang, Liangliang Liu, Zhiquan Zhang, Kai Wang, Libo Li, Weiwei Chen, Kefei 

作者机构：Shanghai University of Electric Power College of Computer Science and Technology Shanghai201306 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China Jinan University College of Cyber Security Guangzhou510632 China Hainan University School of Cryptology Haikou570228 China Hangzhou Normal University Department of Mathematics Hangzhou310036 China 

出 版 物：《IEEE Internet of Things Journal》 (IEEE Internet Things J.)

年 卷 期：2025年第12卷第9期

页      面：11664-11675页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

基　　金：This work was supported in part by the Open Fund of Advanced Cryptography and System Security Key Laboratory of Sichuan Province under Grant SKLACSS-202311 and Grant SKLACSS-202310 in part by the National Natural Science Foundation of China under Grant 62372285, Grant 62302288, Grant 62032025, and Grant 61932011 and in part by the Shanghai Rising-Star Program under Grant 22QA1403800 

主　　题：Data aggregation 

摘      要：While the collection of users’ live or periodic electricity consumption data brings significant advantages for the operation of smart grids, it also heightens the risk of user privacy leakage. Numerous data aggregation schemes have been proposed to address this issue. However, most of these schemes either fail to accommodate the need for multifunctional data analysis or rely on a trusted third party (TTP). Given the efficient data processing capabilities offered by fog computing, we propose a blockchain-based privacy-preserving data aggregation (BPRM) scheme supporting multifunctionality for fog-assisted smart grid without TTP. This scheme ensures data confidentiality and data integrity while providing various statistical functions. In addition, we implement a consensus mechanism between smart meters, further enhancing the security and robustness of the smart grid system. Moreover, not only does the proposed the batch verification reduce the authentication costs but also support error detection in signatures. With BPRM, data center can calculate multiple statistical functions, achieving a win-win strategy. Extensive security and performance analyses demonstrate that BPRM can withstand various security threats and effectively protect user privacy while maintaining efficiency in both computational and communication overhead. © 2014 IEEE.