计算机科学
数据聚合器
智能电网
稳健性(进化)
分布式计算
数据传输
匿名
认证(法律)
信息隐私
安全性分析
计算机网络
计算机安全
无线传感器网络
生态学
生物化学
化学
基因
生物
作者
Jingwei Liu,Haoze Wang,Jiajia Bao,Rong Sun,Xiaojiang Du,Mohsen Guizani
标识
DOI:10.1109/jiot.2024.3352558
摘要
The increasing demand for intelligent management in modern power systems has emphasized the importance of smart grids, which facilitate real-time analysis and management through data aggregation. Fog computing provides efficient data processing and low-latency transmission for data aggregation. However, fog-assisted smart grids still face significant challenges, including privacy leakage, calculation limitations, and system stability issues. In response to these obstacles, we propose a robust and privacy-enhanced multidimensional data aggregation (RPMDA) scheme. Specifically, the Chinese Remainder Theorem is used to improve the efficiency of processing multidimensional data, combined with an innovative double-masking method to cope with secure data aggregation. For the purpose of reliable authentication, a conditional anonymous certificateless signature algorithm is designed in RPMDA, where the pseudonym generation mechanism ensures the conditional anonymity of smart meters. Besides, our scheme incorporates robustness, ensuring that the aggregated results remain unaffected even if smart meters malfunction. Compared to the existing solutions, RPMDA shows superior performance while meeting security requirements.
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