基于秘密共享的电力数据隐私保护方法

Boyu Liu, Wencui Li, Xinyan Wang, Ningxi Song, Zheng Zhou
{"title":"基于秘密共享的电力数据隐私保护方法","authors":"Boyu Liu, Wencui Li, Xinyan Wang, Ningxi Song, Zheng Zhou","doi":"10.1109/ICPECA60615.2024.10471096","DOIUrl":null,"url":null,"abstract":"The issue of privacy in electrical power data within smart grids has drawn increasing attention, with power data leakage posing a serious threat to users' personal privacy. Addressing these concerns, this paper proposes a power data privacy protection method based on secret sharing. Firstly, the method utilizes nodes elected through the leader election algorithm in the Raft protocol to replace traditional aggregators for data verification and aggregation operations. This eliminates the need for a trusted third party and enables fault tolerance for intermediate nodes. Secondly, the method incorporates a dynamic secret sharing homomorphic scheme to achieve secure data aggregation, ensuring that even internal attackers can only access aggregated data without obtaining individual power consumption details. Moreover, the scheme employs batch verification techniques to enhance signature verification speed. Experimental analysis indicates that this method exhibits lower computational and communication overhead compared to alternative approaches.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"10 3","pages":"1366-1370"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Power Data Privacy Protection Method Based on Secret Sharing\",\"authors\":\"Boyu Liu, Wencui Li, Xinyan Wang, Ningxi Song, Zheng Zhou\",\"doi\":\"10.1109/ICPECA60615.2024.10471096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The issue of privacy in electrical power data within smart grids has drawn increasing attention, with power data leakage posing a serious threat to users' personal privacy. Addressing these concerns, this paper proposes a power data privacy protection method based on secret sharing. Firstly, the method utilizes nodes elected through the leader election algorithm in the Raft protocol to replace traditional aggregators for data verification and aggregation operations. This eliminates the need for a trusted third party and enables fault tolerance for intermediate nodes. Secondly, the method incorporates a dynamic secret sharing homomorphic scheme to achieve secure data aggregation, ensuring that even internal attackers can only access aggregated data without obtaining individual power consumption details. Moreover, the scheme employs batch verification techniques to enhance signature verification speed. Experimental analysis indicates that this method exhibits lower computational and communication overhead compared to alternative approaches.\",\"PeriodicalId\":518671,\"journal\":{\"name\":\"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)\",\"volume\":\"10 3\",\"pages\":\"1366-1370\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPECA60615.2024.10471096\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPECA60615.2024.10471096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

智能电网中的电力数据隐私问题日益受到关注,电力数据泄露对用户的个人隐私构成了严重威胁。针对这些问题,本文提出了一种基于秘密共享的电力数据隐私保护方法。首先,该方法利用 Raft 协议中的领导者选举算法选出的节点来代替传统的聚合器进行数据验证和聚合操作。这消除了对可信第三方的需求,并实现了中间节点的容错。其次,该方法采用动态秘密共享同态方案来实现安全的数据聚合,确保即使是内部攻击者也只能访问聚合数据,而无法获取单个功耗细节。此外,该方案还采用了批量验证技术,以提高签名验证速度。实验分析表明,与其他方法相比,该方法的计算和通信开销更低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Power Data Privacy Protection Method Based on Secret Sharing
The issue of privacy in electrical power data within smart grids has drawn increasing attention, with power data leakage posing a serious threat to users' personal privacy. Addressing these concerns, this paper proposes a power data privacy protection method based on secret sharing. Firstly, the method utilizes nodes elected through the leader election algorithm in the Raft protocol to replace traditional aggregators for data verification and aggregation operations. This eliminates the need for a trusted third party and enables fault tolerance for intermediate nodes. Secondly, the method incorporates a dynamic secret sharing homomorphic scheme to achieve secure data aggregation, ensuring that even internal attackers can only access aggregated data without obtaining individual power consumption details. Moreover, the scheme employs batch verification techniques to enhance signature verification speed. Experimental analysis indicates that this method exhibits lower computational and communication overhead compared to alternative approaches.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Research on Fault Analysis and Remote Fault Diagnosis Technology of New Large Capacity Synchronous Condenser An Integrated Target Recognition Method Based on Improved Faster-RCNN for Apple Detection, Counting, Localization, and Quality Estimation Facial Image Restoration Algorithm Based on Generative Adversarial Networks A Data Retrieval Method Based on AGCN-WGAN Long Term Electricity Consumption Forecast Based on DA-LSTM
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1