GuardGrid: A Queriable and Privacy-Preserving Aggregation Scheme for Smart Grid via Function Encryption

Smart grids have revolutionized electricity management by leveraging real-time consumption data, enabling more efficient power control through advanced algorithms. However, this transformation raises significant privacy and security concerns due to the extensive collection of user data. Current solutions face challenges, such as aggregator gateway misbehavior, lack of support for function queries, and the need to balance privacy with efficiency. In this article, we propose FEHH, a novel scheme that ensures both privacy preservation and verifiable aggregation. It allows multiple aggregators to perform inner-product computations on encrypted data while safeguarding the aggregated results from the aggregator. Additionally, it supports verification of aggregated data’s correctness using Linear Homomorphic Hash. Building on FEHH, we introduce GuardGrid, a privacy-preserving aggregation scheme for smart grids that inherits FEHH’s core features and adds support for essential arithmetic operations necessary for function queries. This allows cloud servers to respond to queries from either the control center or users without compromising data confidentiality. Experimental results show that the encryption overhead of GuardGrid is only 7% of that of the PPDA scheme, and its communication overhead is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$123\times $ </tex-math></inline-formula> less. These results demonstrate that GuardGrid significantly reduces computation and communication costs, providing a more sustainable and cost-effective smart grid solution.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-02-07
DOI
https://doi.org/10.1109/jiot.2025.3539724
Citations
6
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
7.29
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article

GuardGrid: A Queriable and Privacy-Preserving Aggregation Scheme for Smart Grid via Function Encryption

Weicong Huang, Xinyuan Qian, Hongwei Li, Hanxiao Chen et al.
6 citations
IEEE Internet of Things Journal
Smart Grid Security and Resilience
7.29
article

GuardGrid: A Queriable and Privacy-Preserving Aggregation Scheme for Smart Grid via Function Encryption

Weicong Huang, Xinyuan Qian, Hongwei Li, Hanxiao Chen, Pengfei Yu, Ran Zhang
article en
6 citations

Abstract

Smart grids have revolutionized electricity management by leveraging real-time consumption data, enabling more efficient power control through advanced algorithms. However, this transformation raises significant privacy and security concerns due to the extensive collection of user data. Current solutions face challenges, such as aggregator gateway misbehavior, lack of support for function queries, and the need to balance privacy with efficiency. In this article, we propose FEHH, a novel scheme that ensures both privacy preservation and verifiable aggregation. It allows multiple aggregators to perform inner-product computations on encrypted data while safeguarding the aggregated results from the aggregator. Additionally, it supports verification of aggregated data’s correctness using Linear Homomorphic Hash. Building on FEHH, we introduce GuardGrid, a privacy-preserving aggregation scheme for smart grids that inherits FEHH’s core features and adds support for essential arithmetic operations necessary for function queries. This allows cloud servers to respond to queries from either the control center or users without compromising data confidentiality. Experimental results show that the encryption overhead of GuardGrid is only 7% of that of the PPDA scheme, and its communication overhead is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$123\times $ </tex-math></inline-formula> less. These results demonstrate that GuardGrid significantly reduces computation and communication costs, providing a more sustainable and cost-effective smart grid solution.

IEEE Internet of Things JournalVol. 12(11)
Electric Power Research Institute (US), University of Electronic Science and Technology of China (CN)
Openalex Percentile: Top 3%
Smart Grid Security and Resilience
7.29
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