走向实用的隐私保护协议

IF 1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS IT-Information Technology Pub Date : 2022-04-01 DOI:10.1515/itit-2022-0005
Daniel Demmler
{"title":"走向实用的隐私保护协议","authors":"Daniel Demmler","doi":"10.1515/itit-2022-0005","DOIUrl":null,"url":null,"abstract":"Abstract Protecting users’ privacy in digital systems becomes more complex and challenging over time, as the amount of stored and exchanged data grows steadily and systems become increasingly involved and connected. Two techniques that try to approach this issue are the privacy-preserving protocols secure multi-party computation (MPC) and private information retrieval (PIR), which aim to enable practical computation while simultaneously keeping sensitive data private. In the dissertation [Daniel Demmler. “Towards Practical Privacy-Preserving Protocols”. Diss. Darmstadt: Technische Universität, 2018. url: http://tuprints.ulb.tu-darmstadt.de/8605/], summarized in this article, we present results showing how real-world applications can be executed in a privacy-preserving way. This is not only desired by users of such applications, but since 2018 also based on a strong legal foundation with the GDPR in the European Union, that enforces privacy protection of user data by design.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Towards practical privacy-preserving protocols\",\"authors\":\"Daniel Demmler\",\"doi\":\"10.1515/itit-2022-0005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Protecting users’ privacy in digital systems becomes more complex and challenging over time, as the amount of stored and exchanged data grows steadily and systems become increasingly involved and connected. Two techniques that try to approach this issue are the privacy-preserving protocols secure multi-party computation (MPC) and private information retrieval (PIR), which aim to enable practical computation while simultaneously keeping sensitive data private. In the dissertation [Daniel Demmler. “Towards Practical Privacy-Preserving Protocols”. Diss. Darmstadt: Technische Universität, 2018. url: http://tuprints.ulb.tu-darmstadt.de/8605/], summarized in this article, we present results showing how real-world applications can be executed in a privacy-preserving way. This is not only desired by users of such applications, but since 2018 also based on a strong legal foundation with the GDPR in the European Union, that enforces privacy protection of user data by design.\",\"PeriodicalId\":43953,\"journal\":{\"name\":\"IT-Information Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2022-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IT-Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/itit-2022-0005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IT-Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/itit-2022-0005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 1

摘要

摘要随着时间的推移,随着存储和交换的数据量稳步增长,以及系统越来越多地参与和连接,在数字系统中保护用户隐私变得更加复杂和具有挑战性。试图解决这一问题的两种技术是隐私保护协议——安全多方计算(MPC)和私有信息检索(PIR),它们旨在实现实际计算,同时保持敏感数据的私有性。论文[Daniel Demmler,“走向实用的隐私保护协议”,德国达姆施塔特工业大学,2018。网址:http://tuprints.ulb.tu-darmstadt.de/8605/],在本文中进行了总结,我们展示了如何以保护隐私的方式执行现实世界中的应用程序的结果。这不仅是此类应用程序的用户所希望的,而且自2018年以来,这也是基于欧盟GDPR的强大法律基础,GDPR通过设计强制保护用户数据的隐私。
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
Towards practical privacy-preserving protocols
Abstract Protecting users’ privacy in digital systems becomes more complex and challenging over time, as the amount of stored and exchanged data grows steadily and systems become increasingly involved and connected. Two techniques that try to approach this issue are the privacy-preserving protocols secure multi-party computation (MPC) and private information retrieval (PIR), which aim to enable practical computation while simultaneously keeping sensitive data private. In the dissertation [Daniel Demmler. “Towards Practical Privacy-Preserving Protocols”. Diss. Darmstadt: Technische Universität, 2018. url: http://tuprints.ulb.tu-darmstadt.de/8605/], summarized in this article, we present results showing how real-world applications can be executed in a privacy-preserving way. This is not only desired by users of such applications, but since 2018 also based on a strong legal foundation with the GDPR in the European Union, that enforces privacy protection of user data by design.
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
IT-Information Technology
IT-Information Technology COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
3.80
自引率
0.00%
发文量
29
期刊最新文献
Wildfire prediction for California using and comparing Spatio-Temporal Knowledge Graphs Machine learning in AI Factories – five theses for developing, managing and maintaining data-driven artificial intelligence at large scale Machine learning applications Machine learning in sensor identification for industrial systems Machine learning and cyber security
×
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