期刊文献+

基于概率的动态视图安全发布方法

Security Dissemination Methods Based on Probability for Dynamic Views
在线阅读 下载PDF
导出
摘要 视图发布的动态性和连续性使得视图间互相联系和影响。静态视图安全研究无法适应实际应用,如何保证动态视图的安全发布亟待解决。为了解决这个问题,首先提出了可能世界构造方法和隐私泄露概率计算方法,并给出了各种视图合并情况下的隐私泄露概率计算公式。然后,从相对安全的角度出发,给出了动态视图的安全判定公式。在此基础上,给出了动态视图的安全发布方法。所提方法能保证相对安全基础上的最大程度视图发布。 Views can restrict database access on specifically attributes and tuples,so publishing views can reduce the possiblity of privacy disclosure.Howevere,the data owner will publish various views based on different application on different time,the dynamic and continuity of view dissemination made mutual contact and mutual influence among views.Considering the privacy disclosure of the publishing views themselves,which called static privacy disclosure,can not measure the disclosure accurately and can not adapt to the practical application,how to guarantee the security of the dynamic views dissemination must be resolved.To solve this problem,at first,the construction method of possible worlds and calculation method of privacy disclosure probability were propoded,and the calculating formulas of privacy disclosure probability under differrent conditions of views merging were presented.Then,the security determination formula for dynamic views was proposed from the point of relative sefe of view.Based on this,the safety dissemination method for dynamic views was presented,which can guarantee maximum level of views publishing upon relatively safe.
出处 《计算机科学》 CSCD 北大核心 2011年第9期158-163,167,共7页 Computer Science
基金 国家自然科学基金(60773100 61070032) 河北省自然科学基金(F2009000475) 河北科技师范学院科研创新团队建设经费(CXTD2010-05)资助
关键词 视图 安全 概率 隐私泄露 Views Security Probability Privacy disclosure
  • 相关文献

参考文献11

  • 1Sweeney L. K-Anonymity: A model for protecting privacy [J].In' l Journal on Uncertainty, Fuzziness and Knowledge-Based Systems, 2002,10 (5) : 557-570.
  • 2Dalenius T, Reiss S. Data swapping:A technique for disclosure control [J]. Journal of Statistical Planning and Inference, 1982,6 (1) :73-85.
  • 3Halevy A. Answering Queries Using Views: A survey [J]. VL- DB Journal, 2001,10 (4) : 270-294.
  • 4Bancilhon F, Spyrators N. Protection of Information in Relational Data Bases[C]//VLDB. Tokyo. Japan, 1977 : 494-500.
  • 5Samarati P,Sweeney L. Protecting Privacy When Disclosing Information:k-anonymity and Its Enforcement through Generalization and SuppressionER3. SRL-CSL-98-04. SRI Computer Science Laboratory, 1998.
  • 6Miklau G, Suciu D. A Formal Analysis of Information Disclosure in Data Exchange[C]//Proceedings of the 20th ACM SIGMOD International Conference on Management of Data. Orlando, USA, 2004: 507-534.
  • 7Dalvi N, Miklau G, Suciu D. Asymptotic Conditional Probabilities for Conjunctive Queries [C]// Proceedings of the Sixth International Conference on Database Theory. Edinburgh, UK, 2002 : 289-305.
  • 8Sweeney L. Achieving k-anonymity privacy protection using gen-e ralization and suppression [J]. Uncertainty, Fuzziness and Knowledge-based Systems, 2002,10(5) : 571-578.
  • 9Sweeney L. K-anonymity: A Model for Protecting Privacy[J]. Int'l Journal on Uncertainty, Fuzziness, and Knowledgebased Systems, 2002,10(5): 557-570.
  • 10Yao Chao, Wang Xiao-yang Scan, et al. Checking for K-Anonymity Violation by Views[C]//VLDB. 2005 : 910-921.

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