期刊文献+

数据共享应用中的隐私保护方法 被引量:2

Privacy preserving in data sharing applications
下载PDF
导出
摘要 为解决数据共享应用中的隐私保护问题和提高数据共享的可用性,提出一种以用户为中心的隐私保护模型.在该模型中,用户可以通过关键字和特征的选取对隐私信息进行自主设置,并采用基于信任的方法来确定共享数据对象可获得的隐私量.当共享数据中包含的隐私量超过共享对象可获得的范围后,通过替换的方法来保护用户隐私.仿真实验表明,对比基于访问控制的隐私保护法,该模型在数据共享应用中能够有效保护隐私并保证较高的数据共享可用性. To solve the problem of privacy preservation while maintaining a high degree of data sharing in applications,a user-centric privacy preservation model is proposed.In the model,users are allowed to set their privacy through selecting key words and special characteristics and a trust based method is used to determine how much privacy entropy that the data sharing entities can get.If the privacy entropy is out of the range that the data sharing entities can afford,a substitution method is used to help preserve privacy.Simulation results show that the method proposed can protect privacy more effectively than methods based on access control while offering a higher degree of data sharing.
出处 《东南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2011年第2期233-236,共4页 Journal of Southeast University:Natural Science Edition
基金 北京市教委科研资助项目(KM201010005027)
关键词 隐私保护 信任 替换 数据共享 privacy preserving trust substitution data sharing
  • 相关文献

参考文献11

  • 1di Crescenzo G, Lipton R J. Social network privacy via evolving access control [ C ]//2009 Wireless Algo- rithms, Systems, and Applications. Boston, MA, USA: 2009:551 -560.
  • 2Lu Y, Weichao W, Bhargava B, et al. Trust-based privacy preservation for peer-to-peer data sharing [ J ]. IEEE Transactions on Systems, Man & Cybernetics Part A ( Systems & Humans) , 2006, 36 ( 3 ) : 498 - 502.
  • 3Lara G, Arnaiz L, Alvarez F, et al. Protected seamless content delivery in P2P wireless and wired networks- seamless content delivery in the future mobile internet [ J]. IEEE Wireless Communications, 2009, 16 ( 15 ) : 50 - 57.
  • 4Iguchi M, Goto S. Privacy-conscious P2P data sharing scheme with bogus profile distribution [ J]. Web Intelli- gence and Agent Systems, 2009, 7 (2) : 209 - 222.
  • 5Jawad M, Serrano-Alvarado P, Valduriez P. Protecting data privacy in structured P2P networks [ C ]//International Conference on Data Management in Grid and Peer-to-Peer Systems. Linz, Austria, 2009:85-98.
  • 6Dong-Hee S. The effects of trust, security and privacy in social networking: a security-based approach to un- derstand the pattern of adoption [ J ]. Interacting with Computers, 2010, 22 (5) :428 - 438.
  • 7Chi Z, Jinyuan S, Xiaoyan Z, et al. Privacy and security for online social networks: challenges and opportunities [J]. IEEENetwork, 2010, 24(4): 13-18.
  • 8Leucio A C, Refik M, Thorsten S. Sefebook: a privacy- preserving online social network leveraging on real-life trust [J]. IEEE Communications Magazine, 2009, 47 (12) :94- 101.
  • 9王慧.Privacy-Preserving Data Sharing in Cloud Computing[J].Journal of Computer Science & Technology,2010,25(3):401-414. 被引量:9
  • 10Gao F, He J, Peng S, et al. An approach for privacy protection based on ontology [ C ]//2nd International Conference on Networks Security, Wireless Communications and Trusted Computing. Wuhan, China, 2010 : 397 -400.

二级参考文献24

  • 1Weiss A. Computing in the clouds. NetWorker, Dec. 2007, 11(4): 16-25.
  • 2Hayes B. Cloud computing. Communications of the ACM, 2008, 51(7): 9-11.
  • 3Nergiz M E, Atzori M, Clifton C W. Hiding the presence of individuals from shared databases. In Proc. ACM's Special Interest Group on Management of Data ( SIGMOD 2007), Beijing, China, June 11-17, 2007, pp.665-676.
  • 4Samarati P, Sweeney L. Generalizing data to provide anonymity when disclosing information. In Proc. ACM International Conference on Principles of Database Systems (PODS), Seattle, USA, June 1-4, 1998, p.188.
  • 5Samarati P, Sweeney L. Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression. Technical Report, SRI International, 1998.
  • 6Sweeney L. k-anonymity: A model for protecting privacy. International Journal on Uncertainty, Fuzziness and Knowledge-Based Systems, 2002, 10(5): 557-570.
  • 7Machanavajjhala A, Gehrke J, Kifer D, Venkitasubrama- niam M. l-diversity: Privacy beyond k-anonymity. In Proc. International Conference on Data Engineering Conference (ICD), Atlanta, USA, Apr. 2006, p.24.
  • 8Xiao X, Tao Y. Anatomy: Simple and effective privacy preservation. In Proc. Very Large Data Base Conference (VLDB), Seoul, Korea, Sept. 12-15, 2006, pp.139-150.
  • 9Zhang Q, Koudas N, Srivastava D, Yu T. Aggregate query answering on anonymized tables. In Proc. International Conferenee on Data Engineering Conference (ICDE), Istanbul, Turkey, Apr. 15-20, 2007, pp.116-125.
  • 10Ghinita G, Karras P, Kalnis P, Mamoulis N. Fast data anonymization with low information loss. In Proc. Very Large Data Base Conference (VLDB), Vienna, Austria, Sept. 23-27, 2007, pp.758-769.

共引文献8

同被引文献3

引证文献2

二级引证文献4

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部