Privacy-preserving multi-dimensional multi-function data aggregation scheme in smart grid
In smart grid, fine-grained user data can be effectively leveraged to support grid operation. However, achieving functional analysis of such data, especially its multi-dimensionalization and multi-functional operation, without compromising user privacy has been identified as an urgent problem. Most...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
POSTS&TELECOM PRESS Co., LTD
2025-06-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2025037 |
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| Summary: | In smart grid, fine-grained user data can be effectively leveraged to support grid operation. However, achieving functional analysis of such data, especially its multi-dimensionalization and multi-functional operation, without compromising user privacy has been identified as an urgent problem. Most existing data aggregation schemes were based on the Paillier and BGN encryption systems, which failed to simultaneously address the multi-dimensionalization and multi-functional operation of data. To tackle this issue, a multi-dimensional and multi-functional data aggregation scheme was designed based on semi-homomorphic encryption. This scheme aimed to enable the multi-dimensionalization and multi-functional operation of meter data while protecting user privacy. The mechanism of partial homomorphic encryption was introduced, and blinding factor and hash function techniques were utilized. These enhancements significantly improved data confidentiality and utility. Security analysis indicates that the scheme is robust against chosen ciphertext attacks. In terms of computational efficiency, it outperforms existing schemes based on the Paillier encryption system. |
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| ISSN: | 2096-109X |