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Enabling Efficient and Malicious Secure Data Aggregation in Smart Grid With False Data Detection
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DOI：10.1109/TSG.2023.3316730.png)
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As the next-generation power grid, the smart grid has significantly improved dependability, flexibility, and efficiency compared with the traditional power grid. However, due to increasingly diverse application requirements, it faces challenges on balancing data privacy, efficiency, and robustness. In this paper, we present a fog computing-based smart grid model. In addition, based on the proposed model, we construct an efficient and privacy-preserving scheme that supports malicious secure smart grid usage data aggregation communication. To our best knowledge, this is the first concrete smart grid solution that concurrently achieves secure aggregation communication, data privacy, and data robustness (e.g., false data detection). Specifically, benefiting from Boolean/Arithmetic secret-sharing methods, our proposed scheme allows home users to report their electricity usage data to the cloud and fogs securely. Besides, a false data detection protocol is proposed to resist false data injection attacks launched by malicious home users. Theoretical analysis and experimental implementation show that our scheme efficiently achieves data security, anonymity, and robustness.
Keyword:
Smart grids
Cloud computing
Computational modeling
Smart meters
Data aggregation
Robustness
Data privacy
Smart grid
false data detection
robustness
privacy-preserving
malicious secure
期刊
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9.8
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5.7K
被引数:
4.3W
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