先进计量基础设施的差分私有数据传输方案

Li Yan, Chao Ma, Cong Wang, Ziqing Zhu, Gaozhou Wang, Huijian Wang
{"title":"先进计量基础设施的差分私有数据传输方案","authors":"Li Yan, Chao Ma, Cong Wang, Ziqing Zhu, Gaozhou Wang, Huijian Wang","doi":"10.1109/PIC53636.2021.9687013","DOIUrl":null,"url":null,"abstract":"Traditional energy consumption data collection is usually deployed with weak security and privacy protection measures, resulting in high risks of data leakage and unauthorized access. To alleviate this problem, we propose a secure and privacy-preserving data transmission scheme (called DPDT) for advanced metering infrastructures based on local differential privacy protection and SM4 symmetric encryption algorithm. Specifically, we first protect the privacy of each client’s energy consumption data via the local differential privacy mechanism. Second, we employ the standard SM4 symmetric encryption algorithm to encrypt the aggregated data, in purpose of ensuring the data transmission. Further, we strictly prove the security of the proposed DPDT scheme, and verify the efficacy via extensive experiments.","PeriodicalId":297239,"journal":{"name":"2021 IEEE International Conference on Progress in Informatics and Computing (PIC)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Differentially Private Data Transmission Scheme for Advanced Metering Infrastructures\",\"authors\":\"Li Yan, Chao Ma, Cong Wang, Ziqing Zhu, Gaozhou Wang, Huijian Wang\",\"doi\":\"10.1109/PIC53636.2021.9687013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional energy consumption data collection is usually deployed with weak security and privacy protection measures, resulting in high risks of data leakage and unauthorized access. To alleviate this problem, we propose a secure and privacy-preserving data transmission scheme (called DPDT) for advanced metering infrastructures based on local differential privacy protection and SM4 symmetric encryption algorithm. Specifically, we first protect the privacy of each client’s energy consumption data via the local differential privacy mechanism. Second, we employ the standard SM4 symmetric encryption algorithm to encrypt the aggregated data, in purpose of ensuring the data transmission. Further, we strictly prove the security of the proposed DPDT scheme, and verify the efficacy via extensive experiments.\",\"PeriodicalId\":297239,\"journal\":{\"name\":\"2021 IEEE International Conference on Progress in Informatics and Computing (PIC)\",\"volume\":\"136 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Progress in Informatics and Computing (PIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PIC53636.2021.9687013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Progress in Informatics and Computing (PIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIC53636.2021.9687013","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

传统的能耗数据采集通常部署了较弱的安全和隐私保护措施,导致数据泄露和未经授权访问的风险较高。为了缓解这一问题,我们提出了一种基于本地差分隐私保护和SM4对称加密算法的高级计量基础设施的安全隐私数据传输方案(DPDT)。具体而言,我们首先通过本地差异隐私机制保护每个客户端的能耗数据隐私。其次,我们采用标准的SM4对称加密算法对聚合数据进行加密,以保证数据的传输。此外,我们严格证明了所提出的DPDT方案的安全性,并通过大量的实验验证了其有效性。
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 Differentially Private Data Transmission Scheme for Advanced Metering Infrastructures
Traditional energy consumption data collection is usually deployed with weak security and privacy protection measures, resulting in high risks of data leakage and unauthorized access. To alleviate this problem, we propose a secure and privacy-preserving data transmission scheme (called DPDT) for advanced metering infrastructures based on local differential privacy protection and SM4 symmetric encryption algorithm. Specifically, we first protect the privacy of each client’s energy consumption data via the local differential privacy mechanism. Second, we employ the standard SM4 symmetric encryption algorithm to encrypt the aggregated data, in purpose of ensuring the data transmission. Further, we strictly prove the security of the proposed DPDT scheme, and verify the efficacy via extensive experiments.
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
The Construction of Learning Diagnosis and Resources Recommendation System Based on Knowledge Graph Classification of Masonry Bricks Using Convolutional Neural Networks – a Case Study in a University-Industry Collaboration Project Optimal Scale Combinations Selection for Incomplete Generalized Multi-scale Decision Systems Application of Improved YOLOV4 in Intelligent Driving Scenarios Research on Hierarchical Clustering Undersampling and Random Forest Fusion Classification Method
×
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