Smart and Practical Privacy-Preserving Data Aggregation for Fog-Based Smart Grids

With the increasingly powerful and extensive deployment of edge devices, edge/fog computing enables customers to manage and analyze data locally, and extends computing power and data analysis applications to network edges. Meanwhile, as the next generation of the power grid, the smart grid can achie...

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Veröffentlicht in:IEEE transactions on information forensics and security 2021, Vol.16, p.521-536
Hauptverfasser: Zhao, Shuai, Li, Fenghua, Li, Hongwei, Lu, Rongxing, Ren, Siqi, Bao, Haiyong, Lin, Jian-Hong, Han, Song
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container_title IEEE transactions on information forensics and security
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creator Zhao, Shuai
Li, Fenghua
Li, Hongwei
Lu, Rongxing
Ren, Siqi
Bao, Haiyong
Lin, Jian-Hong
Han, Song
description With the increasingly powerful and extensive deployment of edge devices, edge/fog computing enables customers to manage and analyze data locally, and extends computing power and data analysis applications to network edges. Meanwhile, as the next generation of the power grid, the smart grid can achieve the goal of efficiency, economy, security, reliability, use safety and environmental friendliness for the power grid. However, privacy and secure issues in fog-based smart grid communications are challenging. Without proper protection, customers' privacy will be readily violated. This article presents a smart and practical Privacy-preserving Data Aggregation (PDA) scheme with smart pricing and packing method for fog-based smart grids, which achieves diversified tariffs, multifunctional statistics and efficiency. Especially, we first propose a smart PDA scheme with Smart Pricing (PDA-SP). With PDA-SP, the Control Center (CC) can compute more complex and higher-order aggregation statistics to provide various services, provide diversiform pricing strategies and choose a double-winning strategy. Subsequently, we put forward a practical PDA scheme with Packing Method (PDA-PM), which is able to reduce the size of encrypted data and improve performance in performing various secure computations. Moreover, we extend our original packing method and present a more useful packing method, which can handle general vectors with large entries. The security analysis shows that our proposed scheme is secure against many threats. The performance evaluation reveals that the computation and communication overheads of our proposed scheme are effectively reduced by employing the Somewhat Homomorphic Encryption (SHE), and our packing method can further significantly reduce these overheads.
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Subsequently, we put forward a practical PDA scheme with Packing Method (PDA-PM), which is able to reduce the size of encrypted data and improve performance in performing various secure computations. Moreover, we extend our original packing method and present a more useful packing method, which can handle general vectors with large entries. The security analysis shows that our proposed scheme is secure against many threats. 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subjects Additives
Agglomeration
Cloud computing
Customers
Data aggregation
Data analysis
Data management
edge computing
Encryption
fog-based smart grid
Handheld computers
industrial Internet of Things
packing method
Performance enhancement
Performance evaluation
Power
Pricing
Privacy
Security
Smart grid
Smart grids
Smart meters
Smart pricing
somewhat homomorphic encryption
Threat evaluation
title Smart and Practical Privacy-Preserving Data Aggregation for Fog-Based Smart Grids
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