Efficient Secure Data Aggregation for Real-Time Smart Grid Monitoring: A Lightweight Privacy-Preserving Approach

被引:0
作者
Zhang, Jianhong [1 ]
Shi, Chuming [1 ]
机构
[1] North China Univ Technol, Sch Elect Informat & Elect Engn, Beijing 100144, Peoples R China
来源
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS | 2024年
基金
中国国家自然科学基金;
关键词
Data aggregation; Smart meters; Smart grids; Servers; Fault tolerant systems; Fault tolerance; Vectors; Real-time systems; Protocols; Power demand; Asymmetric scalar-product-preserving encryption; data aggregation; fine-grained data aggregation; proxy reencryption; SCHEME; PROTOCOL;
D O I
10.1109/TCSS.2024.3510095
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Data aggregation protocols play a crucial role in enabling real-time monitoring of the smart grid's operational status by the power control center. To ensure robust security, a data aggregation protocol should provide features such as data privacy, fault tolerance, lightweight computation, and fine-grained data aggregation. However, existing data aggregation protocols employing techniques such as homomorphic encryption, masking, or differential privacy fail to deliver these features concurrently. To address this challenge, we propose a novel lightweight privacy-preserving data aggregation scheme based on proxy reencryption and asymmetric scalar product-preserving encryption, in which encryption operations only involve addition and multiplication over the integer field, thus avoiding time-consuming exponentiation and pairing operations and achieving lightweight computation. Furthermore, through the use of an asymmetric scalar-product-preserving encryption scheme, we effectively align aggregation policies while maintaining the privacy of power consumption data. Finally, when compared to three recent data aggregation schemes with analogous structures, experimental results demonstrate that our proposed scheme outperforms others regarding computational and communication overheads, thus enhancing its efficiency.
引用
收藏
页数:11
相关论文
共 25 条
  • [1] [Anonymous], 2015, P 3 INT WORKSH SEC C
  • [2] Danezis G., 2013, P 1 ACM WORKSH SMART, P75
  • [3] Homomorphic Proxy Re-Authenticators and Applications to Verifiable Multi-User Data Aggregation
    Derler, David
    Ramacher, Sebastian
    Slamanig, Daniel
    [J]. FINANCIAL CRYPTOGRAPHY AND DATA SECURITY, FC 2017, 2017, 10322 : 124 - 142
  • [4] Non-linear estimation is easy
    Fliess, Michel
    Join, Cedric
    Sira-Ramirez, Hebertt
    [J]. INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL, 2008, 4 (01) : 12 - 27
  • [5] An efficient data aggregation scheme with local differential privacy in smart grid
    Gai, Na
    Xue, Kaiping
    Zhu, Bin
    Yang, Jiayu
    Liu, Jianqing
    He, Debiao
    [J]. DIGITAL COMMUNICATIONS AND NETWORKS, 2022, 8 (03) : 333 - 342
  • [6] Giry D., 2021, Cryptographic key length recommendations
  • [7] Smart Meter Pinging and Reading Through AMI Two-Way Communication Networks to Monitor Grid Edge Devices and DERs
    Huang, Can
    Sun, Chih-Che
    Duan, Nan
    Jiang, Yuming
    Applegate, Chloe
    Barnes, Peter D.
    Stewart, Emma
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2022, 13 (05) : 4144 - 4153
  • [8] Huang C, 2018, IEEE ICC
  • [9] EPPA: An Efficient and Privacy-Preserving Aggregation Scheme for Secure Smart Grid Communications
    Lu, Rongxing
    Liang, Xiaohui
    Li, Xu
    Lin, Xiaodong
    Shen, Xuemin
    [J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2012, 23 (09) : 1621 - 1631
  • [10] A Secure and Privacy-Preserving Protocol for Smart Metering Operational Data Collection
    Mustafa, Mustafa A.
    Cleemput, Sara
    Aly, Abdelrahaman
    Abidin, Aysajan
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (06) : 6481 - 6490