Secure Query Answering for Outsourced Databases in Cloud Computing

云计算中外包数据库的安全查询应答

基本信息

  • 批准号:
    RGPIN-2014-06027
  • 负责人:
  • 金额:
    $ 3.93万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2018
  • 资助国家:
    加拿大
  • 起止时间:
    2018-01-01 至 2019-12-31
  • 项目状态:
    已结题

项目摘要

Cloud computing is no doubt an effective approach to deal with "big data", through providing on-demand high quality services from powerful and configurable computing resources hosted by a third party called the cloud. One application of cloud computing is "database as a service", where the data owner outsources complex database management systems into the cloud. A major obstacle to this application is the confidentiality of sensitive data since the cloud server is not under the control of the data owner and is untrusted. To protect data privacy and confidentiality, sensitive data must be encrypted before being outsourced to the cloud server. This, however, renders traditional query processing methods (such as indexing) inapplicable because all such methods operate on the plaintext data. Thus, query processing over encrypted data is a new research issue and of paramount importance. **There are three requirements to be addressed. The first is confidentiality, that is, the cloud server should not learn anything other than the query result through storing the data and computing the query. The second is authentication where the user should be able to detect the occurrence of the event if the server does not follow the prescribed protocol or tampers with the data or query result. The third is efficiency where the method should be scalable to data at the cloud scale. This requires indexing and computational methods that work directly on encrypted data without scanning the entire database. Cryptography is traditionally a field addressing the first requirement, but the methods developed do not scale up to the cloud scale because a full scan of database often is required. Recent developments in databases and information retrieval address some of these issues, but to our knowledge, no work has addressed all three requirements. In addition, data grows dynamically and the above requirements must be met over time. Initial studies suggest that a "searchable encryption" that addresses all of the above requirements is possible for certain types of queries under some relaxed requirement of confidentiality. The objective of this proposal is to investigate the trade-off between searchability and confidentiality and propose solutions to searchable encryption for larger classes of queries while providing practically acceptable confidentiality. The innovation of this proposal is combining the techniques from databases, cryptography, and information retrieval, which traditionally has different focuses, to address this challenging problem. The outcome of this project will provide methodologies for more secure execution of cloud computing, therefore, benefit all of the data owners, cloud servers, and data users.
云计算无疑是处理“大数据”的一种有效方法,通过由称为云的第三方托管的强大且可配置的计算资源提供按需的高质量服务。云计算的一个应用是“数据库即服务”,其中数据所有者将复杂的数据库管理系统外包到云中。此应用程序的一个主要障碍是敏感数据的机密性,因为云服务器不受数据所有者的控制,并且不受信任。为了保护数据隐私和机密性,敏感数据必须在外包给云服务器之前进行加密。然而,这使得传统的查询处理方法(如索引)不适用,因为所有这些方法都是对明文数据进行操作的。因此,加密数据的查询处理是一个新的研究课题,具有重要的意义。** 需要满足三个要求。首先是机密性,即云服务器不应该通过存储数据和计算查询来学习查询结果之外的任何东西。第二个是身份验证,如果服务器没有遵循规定的协议或篡改数据或查询结果,用户应该能够检测到事件的发生。第三个是效率,其中该方法应该可扩展到云规模的数据。这需要直接对加密数据工作而无需扫描整个数据库的索引和计算方法。密码学传统上是解决第一个要求的领域,但开发的方法不能扩展到云规模,因为通常需要对数据库进行全面扫描。数据库和信息检索的最新发展解决了其中的一些问题,但据我们所知,没有任何工作解决了所有三个要求。此外,数据是动态增长的,必须随着时间的推移满足上述要求。初步研究表明,在某些宽松的保密要求下,满足上述所有要求的“可搜索加密”对于某些类型的查询是可能的。这项建议的目的是调查的可搜索性和保密性之间的权衡,并提出解决方案,以搜索加密较大类别的查询,同时提供实际上可以接受的保密性。该提案的创新之处在于将数据库、密码学和信息检索等传统上具有不同侧重点的技术相结合,以解决这一具有挑战性的问题。该项目的成果将为云计算的更安全执行提供方法,因此,所有数据所有者,云服务器和数据用户都将受益。

项目成果

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Wang, Ke其他文献

Catalyst-Free C(sp2)-H Borylation through Aryl Radical Generation from Thiophenium Salts via Electron Donor-Acceptor Complex Formation
  • DOI:
    10.1021/acs.orglett.2c03008
  • 发表时间:
    2022-10-03
  • 期刊:
  • 影响因子:
    5.2
  • 作者:
    Li, Bo;Wang, Ke;Rueping, Magnus
  • 通讯作者:
    Rueping, Magnus
FDMAX: An Elastic Accelerator Architecture for Solving Partial Differential Equations
FDMAX:用于求解偏微分方程的弹性加速器架构
Therapeutic Activity of Green Tea Epigallocatechin-3-Gallate on Metabolic Diseases and Non-Alcoholic Fatty Liver Diseases: The Current Updates.
  • DOI:
    10.3390/nu15133022
  • 发表时间:
    2023-07-03
  • 期刊:
  • 影响因子:
    5.9
  • 作者:
    James, Armachius;Wang, Ke;Wang, Yousheng
  • 通讯作者:
    Wang, Yousheng
Stochastic logistic equation with infinite delay (vol 35, pg 812, 2012)
具有无限延迟的随机逻辑方程(第 35 卷,第 812 页,2012 年)
Structural and kinetic analysis of CO2 sorption on NaNO2-promoted MgO at moderate temperatures
  • DOI:
    10.1016/j.cej.2019.04.080
  • 发表时间:
    2019-09-15
  • 期刊:
  • 影响因子:
    15.1
  • 作者:
    Wang, Ke;Zhao, Youwei;Anthony, Edward J.
  • 通讯作者:
    Anthony, Edward J.

Wang, Ke的其他文献

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{{ truncateString('Wang, Ke', 18)}}的其他基金

Privacy Preserving synthesized data releasing via generative adversarial networks
通过生成对抗网络发布的隐私保护合成数据
  • 批准号:
    RGPIN-2019-06119
  • 财政年份:
    2022
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
Privacy Preserving synthesized data releasing via generative adversarial networks
通过生成对抗网络发布的隐私保护合成数据
  • 批准号:
    RGPIN-2019-06119
  • 财政年份:
    2021
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
Privacy Preserving synthesized data releasing via generative adversarial networks
通过生成对抗网络发布的隐私保护合成数据
  • 批准号:
    RGPIN-2019-06119
  • 财政年份:
    2020
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
Privacy Preserving synthesized data releasing via generative adversarial networks
通过生成对抗网络发布的隐私保护合成数据
  • 批准号:
    RGPAS-2019-00081
  • 财政年份:
    2020
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
Privacy Preserving synthesized data releasing via generative adversarial networks
通过生成对抗网络发布的隐私保护合成数据
  • 批准号:
    RGPAS-2019-00081
  • 财政年份:
    2019
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
Privacy Preserving synthesized data releasing via generative adversarial networks
通过生成对抗网络发布的隐私保护合成数据
  • 批准号:
    RGPIN-2019-06119
  • 财政年份:
    2019
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
Secure Query Answering for Outsourced Databases in Cloud Computing
云计算中外包数据库的安全查询应答
  • 批准号:
    RGPIN-2014-06027
  • 财政年份:
    2017
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
Secure Query Answering for Outsourced Databases in Cloud Computing
云计算中外包数据库的安全查询应答
  • 批准号:
    RGPIN-2014-06027
  • 财政年份:
    2016
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
Prediction of distribution feeder outages caused by storms
风暴造成的配电馈线停运预测
  • 批准号:
    445210-2012
  • 财政年份:
    2015
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Collaborative Research and Development Grants
Secure Query Answering for Outsourced Databases in Cloud Computing
云计算中外包数据库的安全查询应答
  • 批准号:
    RGPIN-2014-06027
  • 财政年份:
    2015
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual

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