支持插入加密多映射与卷隐藏

S. Ishihara, Chiemi Watanabe, T. Amagasa
{"title":"支持插入加密多映射与卷隐藏","authors":"S. Ishihara, Chiemi Watanabe, T. Amagasa","doi":"10.1109/SMARTCOMP52413.2021.00058","DOIUrl":null,"url":null,"abstract":"A new threat in encrypted databases, called volume leakage was reported by Kellaris et al. and Grubbs et al., where the volume of data associated with each key in a multi-map is leaked. An existing method addresses this problem by adding noise entries to the multi-map according to differential privacy so that adversaries cannot infer the volume of data. However, it assumes that the data is static and therefore does not support any update operations, such as insertion, deletion, etc. To this problem, this paper proposes a method that enables data insertion in the encrypted multi-map with volume hiding. The basic idea is to use local differential privacy instead of differential privacy in adding noise entries when performing insertions. Besides, we employ cuckoo hashing to perturb the place of insertion, thereby allowing insertions of new items without leaking the volume of entries.However, our proposed method is not suitable for large databases. We consider the use of cloud database in healthcare as a use case. The cloud database is necessary for healthcare in cases such as when multiple medical institutions want to share medical data or when home healthcare providers want to access medical data from outside of hospitals. There are privacy issues if the number of patients for each disease is known. Furthermore, when inserting data of a new patient, we want to hide which disease the patient is suffering from.We conduct experiments to assess the feasibility of the proposed method, and it presents a reasonable performance.","PeriodicalId":330785,"journal":{"name":"2021 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Supporting Insertion in Encrypted Multi-Maps with Volume Hiding\",\"authors\":\"S. Ishihara, Chiemi Watanabe, T. Amagasa\",\"doi\":\"10.1109/SMARTCOMP52413.2021.00058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new threat in encrypted databases, called volume leakage was reported by Kellaris et al. and Grubbs et al., where the volume of data associated with each key in a multi-map is leaked. An existing method addresses this problem by adding noise entries to the multi-map according to differential privacy so that adversaries cannot infer the volume of data. However, it assumes that the data is static and therefore does not support any update operations, such as insertion, deletion, etc. To this problem, this paper proposes a method that enables data insertion in the encrypted multi-map with volume hiding. The basic idea is to use local differential privacy instead of differential privacy in adding noise entries when performing insertions. Besides, we employ cuckoo hashing to perturb the place of insertion, thereby allowing insertions of new items without leaking the volume of entries.However, our proposed method is not suitable for large databases. We consider the use of cloud database in healthcare as a use case. The cloud database is necessary for healthcare in cases such as when multiple medical institutions want to share medical data or when home healthcare providers want to access medical data from outside of hospitals. There are privacy issues if the number of patients for each disease is known. Furthermore, when inserting data of a new patient, we want to hide which disease the patient is suffering from.We conduct experiments to assess the feasibility of the proposed method, and it presents a reasonable performance.\",\"PeriodicalId\":330785,\"journal\":{\"name\":\"2021 IEEE International Conference on Smart Computing (SMARTCOMP)\",\"volume\":\"128 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Smart Computing (SMARTCOMP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMARTCOMP52413.2021.00058\",\"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 Smart Computing (SMARTCOMP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMARTCOMP52413.2021.00058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

Kellaris等人和Grubbs等人报告了加密数据库中的一种新威胁,称为卷泄漏,其中与多映射中每个密钥相关的数据量被泄露。现有的一种方法通过根据差分隐私向多映射中添加噪声条目来解决这个问题,从而使攻击者无法推断数据量。但是,它假设数据是静态的,因此不支持任何更新操作,例如插入、删除等。针对这一问题,本文提出了一种采用卷隐藏的方式在加密多映射中插入数据的方法。基本思想是在执行插入时使用局部差分隐私而不是差分隐私来添加噪声项。此外,我们使用布谷鸟哈希对插入位置进行扰动,从而可以在不泄漏条目体积的情况下插入新条目。然而,我们提出的方法不适合大型数据库。我们将云数据库在医疗保健领域的使用作为一个用例。在多个医疗机构希望共享医疗数据或家庭医疗保健提供商希望从医院外部访问医疗数据等情况下,云数据库对于医疗保健是必要的。如果每种疾病的患者人数已知,就会出现隐私问题。此外,在插入新患者的数据时,我们希望隐藏该患者所患的疾病。通过实验验证了该方法的可行性,并给出了合理的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Supporting Insertion in Encrypted Multi-Maps with Volume Hiding
A new threat in encrypted databases, called volume leakage was reported by Kellaris et al. and Grubbs et al., where the volume of data associated with each key in a multi-map is leaked. An existing method addresses this problem by adding noise entries to the multi-map according to differential privacy so that adversaries cannot infer the volume of data. However, it assumes that the data is static and therefore does not support any update operations, such as insertion, deletion, etc. To this problem, this paper proposes a method that enables data insertion in the encrypted multi-map with volume hiding. The basic idea is to use local differential privacy instead of differential privacy in adding noise entries when performing insertions. Besides, we employ cuckoo hashing to perturb the place of insertion, thereby allowing insertions of new items without leaking the volume of entries.However, our proposed method is not suitable for large databases. We consider the use of cloud database in healthcare as a use case. The cloud database is necessary for healthcare in cases such as when multiple medical institutions want to share medical data or when home healthcare providers want to access medical data from outside of hospitals. There are privacy issues if the number of patients for each disease is known. Furthermore, when inserting data of a new patient, we want to hide which disease the patient is suffering from.We conduct experiments to assess the feasibility of the proposed method, and it presents a reasonable performance.
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:604180095
Book学术官方微信