基于代理辅助ORAM的隐私保护全基因组序列处理

Nikolaos P. Karvelas, Andreas Peter, S. Katzenbeisser, Erik Tews, K. Hamacher
{"title":"基于代理辅助ORAM的隐私保护全基因组序列处理","authors":"Nikolaos P. Karvelas, Andreas Peter, S. Katzenbeisser, Erik Tews, K. Hamacher","doi":"10.1145/2665943.2665962","DOIUrl":null,"url":null,"abstract":"Widespread use and low prices of genomic sequencing bring us into the area of personalized medicine and biostatistics of large cohorts. As the processed genomic data is highly sensitive, Privacy-Enhancing Technologies for genomic data need to be developed. In this work, we present a novel and flexible mechanism for the private processing of whole genomic sequences which is flexible enough to support any query. The basic underlying idea is to store DNA in several small encrypted blocks, use ORAM mechanisms to access the desired blocks in an oblivious manner, and finally run secure two-party protocols to privately compute the desired functionality on the retrieved encrypted blocks. Our construction keeps all sensitive information hidden and reveals only the end result to the legitimate party. Our main technical contribution is the design of a new ORAM that allows for access rights delegation while not requiring the data owner to be online to reshuffle the database. We validate the practicability of our approach through experimental studies.","PeriodicalId":408627,"journal":{"name":"Proceedings of the 13th Workshop on Privacy in the Electronic Society","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":"{\"title\":\"Privacy-Preserving Whole Genome Sequence Processing through Proxy-Aided ORAM\",\"authors\":\"Nikolaos P. Karvelas, Andreas Peter, S. Katzenbeisser, Erik Tews, K. Hamacher\",\"doi\":\"10.1145/2665943.2665962\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Widespread use and low prices of genomic sequencing bring us into the area of personalized medicine and biostatistics of large cohorts. As the processed genomic data is highly sensitive, Privacy-Enhancing Technologies for genomic data need to be developed. In this work, we present a novel and flexible mechanism for the private processing of whole genomic sequences which is flexible enough to support any query. The basic underlying idea is to store DNA in several small encrypted blocks, use ORAM mechanisms to access the desired blocks in an oblivious manner, and finally run secure two-party protocols to privately compute the desired functionality on the retrieved encrypted blocks. Our construction keeps all sensitive information hidden and reveals only the end result to the legitimate party. Our main technical contribution is the design of a new ORAM that allows for access rights delegation while not requiring the data owner to be online to reshuffle the database. We validate the practicability of our approach through experimental studies.\",\"PeriodicalId\":408627,\"journal\":{\"name\":\"Proceedings of the 13th Workshop on Privacy in the Electronic Society\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"35\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 13th Workshop on Privacy in the Electronic Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2665943.2665962\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 13th Workshop on Privacy in the Electronic Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2665943.2665962","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 35

摘要

基因组测序的广泛使用和低价格将我们带入个性化医疗和大队列生物统计领域。由于处理后的基因组数据高度敏感,因此需要开发增强基因组数据隐私的技术。在这项工作中,我们提出了一种新颖而灵活的全基因组序列私人处理机制,该机制足够灵活,可以支持任何查询。基本的基本思想是将DNA存储在几个小的加密块中,使用ORAM机制以遗忘的方式访问所需的块,最后运行安全的两方协议,在检索到的加密块上私下计算所需的功能。我们的结构将所有敏感信息隐藏起来,只向合法方显示最终结果。我们的主要技术贡献是设计了一个新的ORAM,它允许访问权限委托,而不要求数据所有者在线重新洗刷数据库。我们通过实验研究验证了该方法的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Privacy-Preserving Whole Genome Sequence Processing through Proxy-Aided ORAM
Widespread use and low prices of genomic sequencing bring us into the area of personalized medicine and biostatistics of large cohorts. As the processed genomic data is highly sensitive, Privacy-Enhancing Technologies for genomic data need to be developed. In this work, we present a novel and flexible mechanism for the private processing of whole genomic sequences which is flexible enough to support any query. The basic underlying idea is to store DNA in several small encrypted blocks, use ORAM mechanisms to access the desired blocks in an oblivious manner, and finally run secure two-party protocols to privately compute the desired functionality on the retrieved encrypted blocks. Our construction keeps all sensitive information hidden and reveals only the end result to the legitimate party. Our main technical contribution is the design of a new ORAM that allows for access rights delegation while not requiring the data owner to be online to reshuffle the database. We validate the practicability of our approach through experimental studies.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信