Privacy-aware Management of Relational Data
关系数据的隐私意识管理
基本信息
- 批准号:256809816
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:德国
- 项目类别:Research Grants
- 财政年份:2014
- 资助国家:德国
- 起止时间:2013-12-31 至 2017-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This proposal investigates privacy-aware, efficient management of relational data with a star schema. In particular, we consider denormalized, non-aggregated databases containing personal data. Further, we assume a database model where many dimension tables are linked with a large fact table via surrogate keys. Typically, such databases process read operations very frequently, insert- and delete operations must be executed from time to time, but update operations on existing tuples are infrequently processed. We focus on this scenario for three reasons: Firstly, the star schema is a classical database model that is used by numerous recent applications storing personal data, e.g., for data warehousing and mining, to manage transaction histories of customers in an ERP system, or to annotate digital objects with social software approaches like Folksonomies. Secondly, it is particularly important to develop privacy approaches for relational databases with a star schema now, because there is a strong tendency to move such databases into the custody of third parties by using techniques like cloud computing or database-as-a-service. Thirdly, it is unclear how to protect the privacy of the individuals concerned by such databases. There exist privacy approaches for statistical databases, geospatial trajectories, set-valued databases or graph databases, e.g., anonymization approaches like Differential Privacy or architectures like Hippocratic Databases. Nevertheless, such approaches cannot be deployed readily for relational databases with a star schema. Our objective is to develop a privacy-aware database management system for relational data with a star schema (RDSS) that handles queries, insert- and delete operations efficiently. Thus, every user should be able to know and to determine who is able to access which personal values relating to the user. For this purpose, we want to create privacy methods for RDSS that (1) conceal the relation of the data to the individual concerned, or (2) restrict the access to sensitive data. In this context, we want to design system architectures, algorithms, database models and attacker models. Thus, we strive for a holistic approach that takes into account that privacy challenges might arise from many aspects of storing, transferring and processing personal data in RDSS.
该提案研究了使用星星模式的关系数据的隐私感知的高效管理。特别是,我们考虑包含个人数据的非规范化,非聚合数据库。此外,我们假设一个数据库模型,其中许多维度表通过代理键与一个大的事实表链接。通常,这样的数据库非常频繁地处理读操作,插入和删除操作必须不时地执行,但是对现有元组的更新操作很少被处理。我们关注这种情况有三个原因:首先,星星模式是一种经典的数据库模型,被许多最近存储个人数据的应用程序所使用,例如,用于数据仓库和挖掘,在ERP系统中管理客户的交易历史,或使用社交软件方法(如Folksonomies)注释数字对象。其次,现在为具有星星模式的关系数据库开发隐私方法尤为重要,因为通过使用云计算或数据库即服务等技术将此类数据库转移到第三方保管中的趋势很强。第三,不清楚如何保护这些数据库所涉个人的隐私。存在用于统计数据库、地理空间轨迹、集值数据库或图形数据库的隐私方法,例如,匿名化方法,如差分隐私或架构,如希波克拉底数据库。然而,这样的方法不能容易地部署到具有星星模式的关系数据库。我们的目标是开发一个具有隐私意识的数据库管理系统,关系数据与星星模式(RDSS),有效地处理查询,插入和删除操作。因此,每个用户都应该能够知道并确定谁能够访问与该用户相关的哪些个人值。为此,我们希望为RDSS创建隐私方法,(1)隐藏数据与相关个人的关系,或(2)限制对敏感数据的访问。在这种情况下,我们希望设计系统架构,算法,数据库模型和攻击者模型。因此,我们努力采取全面的方法,考虑到在RDSS中存储,传输和处理个人数据的许多方面可能会出现隐私挑战。
项目成果
期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
On Preserving Secrecy in Mobile Social Networks
- DOI:10.5445/ir/1000096955
- 发表时间:2020-05
- 期刊:
- 影响因子:2.3
- 作者:Gabriela Suntaxi;A. A. E. Ghazi-A.;Klemens Böhm
- 通讯作者:Gabriela Suntaxi;A. A. E. Ghazi-A.;Klemens Böhm
Towards meaningful distance-preserving encryption
- DOI:10.1145/3221269.3223029
- 发表时间:2018-07
- 期刊:
- 影响因子:0
- 作者:Christine Tex;Martin Schäler;Klemens Böhm
- 通讯作者:Christine Tex;Martin Schäler;Klemens Böhm
On Mutual Authorizations: Semantics, Integration Issues, and Performance
关于相互授权:语义、集成问题和性能
- DOI:10.5445/ir/1000093936
- 发表时间:2019
- 期刊:
- 影响因子:0
- 作者:Gabriela Suntaxi;Aboubakr Achraf El Ghazi;Klemens Böhm
- 通讯作者:Klemens Böhm
Mutual Authorizations: Semantics and Integration Issues
相互授权:语义和集成问题
- DOI:10.1145/3322431.3325415
- 发表时间:2019
- 期刊:
- 影响因子:0
- 作者:Gabriela Suntaxi;Aboubakr Achraf El Ghazi;Klemens Böhm
- 通讯作者:Klemens Böhm
Distance-Based Data Mining over Encrypted Data
- DOI:10.1109/icde.2018.00126
- 发表时间:2018-04
- 期刊:
- 影响因子:0
- 作者:Christine Tex;Martin Schäler;Klemens Böhm
- 通讯作者:Christine Tex;Martin Schäler;Klemens Böhm
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Professor Dr.-Ing. Klemens Böhm其他文献
Professor Dr.-Ing. Klemens Böhm的其他文献
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Incentives Engineering für strukturierte P2P-Systeme
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452183896 - 财政年份:
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