Research on data integration privacy preservation mechanism for DaaS

Zhi-gang ZHOU; Hong-li ZHANG; Xiang-zhan YU; Pan-pan LI

doi:10.11959/j.issn.1000-436x.2016076

您当前的位置：

首页 >

文章列表页 >

Research on data integration privacy preservation mechanism for DaaS

academic paper | 更新时间：2024-06-05

- Research on data integration privacy preservation mechanism for DaaS
- Journal of Communications Vol. 37, Issue 4, Pages: 96-106(2016)
- 作者机构：
  
  哈尔滨工业大学计算机网络与信息安全技术研究中心，黑龙江哈尔滨150001
- 作者简介：
- 基金信息：
  
  The National Basic Research Program of China (973 Program)(2011CB302605);The National Natural Science Foundation of China(61173144);The National Natural Science Foundation of China(60903166);The National Natural Science Foundation of China(61100188)
- DOI：10.11959/j.issn.1000-436x.2016076
  CLC： TP393
- Online First：2016-04，
  
  Published：25 April 2016
- 稿件说明：
移动端阅览
Zhi-gang ZHOU, Hong-li ZHANG, Xiang-zhan YU, et al. Research on data integration privacy preservation mechanism for DaaS[J]. Journal of Communications, 2016, 37(4): 96-106.
DOI：

Zhi-gang ZHOU, Hong-li ZHANG, Xiang-zhan YU, et al. Research on data integration privacy preservation mechanism for DaaS[J]. Journal of Communications, 2016, 37(4): 96-106. DOI： 10.11959/j.issn.1000-436x.2016076.

摘要

云计算的出现为多个数据拥有者进行数据集成发布及协同数据挖掘提供了更广阔的平台，在数据即服务模式（DaaS

data as a service）下，集成数据被部署在非完全可信的服务运营商平台上，数据隐私保护成为制约该模式应用和推广的挑战性问题。为防止数据集成时的隐私泄露，提出一种面向 DaaS 应用的两级隐私保护机制。该隐私保护机制独立于具体的应用，将数据属性切分到不同的数据分块中，并通过混淆数据确保数据在各个分块中均衡分布，实现对数据集成隐私保护。通过分析证明该隐私保护机制的合理性，并通过实验验证该隐私保护机制具有较低的计算开销。

Abstract

The emergence of cloud computing provides a broader platform for multiple data owners to make integrated data publishing and collaborative data mining. In data-as-a-service (DaaS) model

integrated data was deployed in a cer-tain cloud platform with an untrusted service provider ta privacy leakage has become the challenge hindering applica-tion and popularization of DaaS model. For protecting privacy in the data integration stage

a two-layer privacy pro-tection mechanism for DaaS-oriented application was given

which was independent ith the specific applications

parti-tioning data attributes into different parts. In addition

the corres ding fake data set was used to assure the balanced distribution of data in each part

which realized privacy protection of data integration. The experimental results indicate that the proposed strategy is feasible

simultaneously has the low computing overhead.

关键词

Keywords

references

周水庚，李丰，陶宇飞，等．面向数据库应用的隐私保护研究综述 [J ] ．计算机学报， 2009 , 32 ( 5 ): 847 - 861 .

ZHOU S G , LI F , TAO Y F , et al . Privacy preservation in database ap-plications: a survey [J ] . Chinese Journal of Computers , 2009 , 32 ( 5 ): 847 - 861 .

田秀霞，王晓玲，高明，等．数据库服务—安全与隐私保护 [J ] ．软件学报， 2010 , 21 ( 5 ): 991 - 1006 .

TIAN X X , WANG X L , GAO M , et al . Database as a ser-vice—security and privacy preserving [J ] . Journal of Software , 2010 , 21 ( 5 ): 991 - 1006 .

CRAIG G . Fully homomorphic encryption using ideal lattices [C ] // The 41st Annual ACM Symposium on Theory of Computing (STOC). Bethesda, MD, USA , c 2009 : 169 - 178 .

SWEENEY L . k-anonymity:a model for protecting privacy [J ] . Inter-national Journal on Uncertainty, Fuzziness and Knowledge Based Systems , 2002 , 10 ( 5 ): 557 - 570 .

WONG R C , LI J , FU A W , et al . (a,k)-anonymity: an en-hanced k-anonymity model for privacy preserving data publishing [C ] // ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD). Philadelphia, PA, USA , c 2006 : 754 - 759 .

JIANG W , CLIFTON C . A secure distributed framework for achieving anonymity [J ] . The International Journal on Very Large Data Bases , 2006 , 15 ( 4 ): 316 - 333 .

CLIFTON C , KANTARCIOGLU , VAIDYA J . Tools for privacy pre-serving distributed data mining [J ] . ACM SIGKDD Explorations , 2003 , 4 ( 2 ): 1 - 7 .

MOHAMMED N , FUNG B C M , DEBBABI M . Anonymity meets game theory: secure data integration with malicious participants [J ] . Very Large Data Bases Journal (VLDBJ), 2011 , 20 ( 4 ): 567 - 588 .

MOHAMMED N , FUNG B C M , et al . Centralized and distrib anonymization for high-dimensional healthcare data [J ] . ACM Trans-actions on Knowledge Discovery from Data (TKDD), 2010 , 4 ( 4 ): 18:1 - 18:33 .

JIANG W , CLIFTON C , KANTARCIOGLU M . Transforming semi-honest protocols to ensure accountability [J ] . Data Knowl Eng , 2008 , 65 ( 1 ): 57 - 74 .

DU W. , HAN Y S , CHEN S . Privacy-preserving multivariate statistic cal analysis: linear regression and classification [C ] // SIAM Interna-tional Conference on Data Mining . Florida , c 2014 : 222 - 233 .

PINKAS B . Cryptographic techniques for privacy-preserving data mining [J ] . ACM SIGKDD Explor News , 2002 , 4 ( 2 ): 12 - 19 .

VAIDYA J , CLIFTON C . Privacy preserving k-means clustering over vertically partitioned data [C ] // The ACM SIGKDD , c 2003 : 206 - 215 .

CIRIANI V , VIMERCATI S , FORESTI S . Fragmentation design for efficient query execution over sensitive distributed databases [C ] // The 29th ICDCS . Canada , c 2009 : 32 - 39 .

CIRIANI V , VIMERCATI S , FORESTI S . Selective data outs for enforcing privacy [J ] . Journal of Computer Security , 2011 , 19 : 531 - 566 .

VIMERCATI S , FORESTI S , JAJODIA S . Fragments and loose asso-ciations: respecting privacy in data publishing [J ] . Proceeding of the VLDB Endowment , 2010 , 3 ( 12 ): 1370 - 1381 .

张坤，李庆忠，史玉良．面向 SaaS 应用的数据组合隐私保护机制研究 [J ] ．计算机学报， 2010 , 33 ( 11 ): 2044 - 2054 .

ZHANG K , LI Q Z , SHI Y L . Research on data combination privacy preservation mechanism for SaaS [J ] . Chinese Journal of Computers , 2010 , 33 ( 11 ): 2044 - 2054 .

ZHANG K , SHI Y , LI Q . Data privacy preserving mechanism based on tenant customization for SaaS [C ] // The International Conference on Multimedia Information Networking and Security . Wuhan, China , c 2009 : 599 - 603 .

OSBORNE M J , RUBINSTEIN A . A course in game theory [M ] . The MIT Press , Cambridge, UK , 1994 .

Views

2025

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Design of periodic deniable ring signcryption scheme based on SM9

Lightweight facial authentication scheme based on the SM4 algorithm for privacy protection

Selective aggregation scheme for multi-dimensional data with type-based verification

Identity privacy and security protection scheme for charitable donations based on group signatures

Privacy-preserving task matching scheme for crowdsourcing

Related Author

Zhang Yanshuo

Kong Jiayin

Zhou Xingyu

Xie Rongna

Qin Xiaohong

ZHANG Xucheng

XIONG Ling

LIU Zhicai

Related Institution

Department of Cryptology Science and Technology, Beijing Electronic Science & Technology Institute

School of Computer and Software Engineering, Xihua University

School of Information Science, Beijing Language and Culture University

School of Computer Science and Technology, Guizhou University

State Key Laboratory of Public Big Data, Ministry of Education

AI问答

⁰