智能电网中隐私保护的多维多函数数据聚合方案

王圆圆; 韩益亮; 吴立强; 李鱼; 姚武军; 吴旭光; 朱率率

doi:10.11959/j.issn.2096-109x.2025037

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智能电网中隐私保护的多维多函数数据聚合方案

学术论文 | 更新时间：2025-06-30

- 智能电网中隐私保护的多维多函数数据聚合方案
- Privacy-preserving multi-dimensional multi-function data aggregation scheme in smart grid
- 网络与信息安全学报 2025年11卷第3期页码：163-174
- 作者机构：
  
  1.武警工程大学密码工程学院，陕西西安 710086
  2.武警工程大学反恐指挥信息工程教育部重点实验室，陕西西安 710086
- 作者简介：
  
  [ "王圆圆（2001- ），女，江西上饶人，武警工程大学硕士生，主要研究方向为密码学和机器学习。" ]
  [ "韩益亮（1977- ），男，甘肃兰州人，武警工程大学教授、博士生导师，主要研究方向为密码学和机密计算。" ]
  [ "吴立强（1986- ），男，陕西蓝田人，武警工程大学讲师，主要研究方向密码学和信息安全。" ]
  [ "李鱼（1995- ），男，重庆丰都人，武警工程大学博士生，主要研究方向为密码学和机器学习。" ]
  [ "姚武军（1986- ），男，湖北随州人，武警工程大学博士生、讲师，主要研究方向为密码学和信息安全。" ]
  [ "吴旭光（1986- ），男，河南商丘人，武警工程大学博士生、讲师，主要研究方向为密码学和信息安全。" ]
  [ "朱率率（1985- ），男，山东淄博人，武警工程大学教授、硕士生导师，主要研究方向为后量子密码和密码分析。" ]
- 基金信息：
  
  The National Defense Technology Innovation Program
- DOI：10.11959/j.issn.2096-109x.2025037
  中图分类号： TP393
- 收稿：2025-02-10，
  
  修回：2025-03-30，
  
  纸质出版：2025-06-25
- 稿件说明：
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王圆圆, 韩益亮, 吴立强, 等. 智能电网中隐私保护的多维多函数数据聚合方案[J]. 网络与信息安全学报, 2025, 11(3): 163-174.

Format: WANG Y Y, HAN Y L, WU L Q, et al. Privacy-preserving multi-dimensional multi-function data aggregation scheme in smart grid[J]. Chinese Journal of Network and Information Security, 2025, 11(3): 163-174.
王圆圆, 韩益亮, 吴立强, 等. 智能电网中隐私保护的多维多函数数据聚合方案[J]. 网络与信息安全学报, 2025, 11(3): 163-174. DOI： 10.11959/j.issn.2096-109x.2025037.

Format: WANG Y Y, HAN Y L, WU L Q, et al. Privacy-preserving multi-dimensional multi-function data aggregation scheme in smart grid[J]. Chinese Journal of Network and Information Security, 2025, 11(3): 163-174. DOI： 10.11959/j.issn.2096-109x.2025037.

摘要

智能电网中精细的用户数据可以有效支撑电网运行。目前，如何在不影响用户隐私的前提下，实现数据的功能性分析，尤其是数据的多维化和多函数操作，是一个亟待解决的问题。现有数据聚合方案大多基于Paillier和BGN加密系统，无法同时兼顾数据的多维化和多函数操作。针对这个问题，设计了一种基于半同态加密的多维多函数数据聚合方案，旨在保护用户隐私的同时，实现电表数据的多维化和多函数操作。该方案通过引入部分同态加密的机制，利用盲化因子和哈希函数技术，增强了数据的机密性和利用率。通过安全性分析证明该方案能够抵抗选择明文攻击，并且在计算效率方面优于基于Paillier加密的方案。

Abstract

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.

关键词

Keywords

references

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