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隐私保护-分布式挖掘中的改进型评价函数 被引量：2

Improved Score Function on Privacy-preserving Distributed Mining
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摘要 隐私保护的目标是要在不精确访问真实原始数据的条件下,如通过病历,对乳腺癌的确诊,得到准确的模型和分析结果。研究了分布式环境下构造贝叶斯网络结构的K2算法的评价函数,并且以密码学中的两方安全计算为基础对该函数进行改进。通过理论分析和实验结果说明了改进的评价函数能够得到与原始的评价函数相同的贝叶斯网络结构。达到了数据垂直分布情况下隐私保护的目的。 The purpose of privacy preservation was to discover accurate patterns without precise access to the original data.For example,the result of breast-cancer could be obtained according to diseases data.The paper researched the score function of K2 Algorithm for constructing the Bayesian Networks in the distributed settings,and improved the score function based on the two-party computation of the cryptographic preliminaries.It could generate the same structures whether original score function or improved score function by the theory analysis and experimental results.The purpose of privacy preserving was reached on vertically partitioned data.
作者 吕品 于文兵
机构地区 武汉工程大学计算机科学与工程学院 武汉工程大学理学院
出处 《武汉理工大学学报》 CAS CSCD 北大核心 2008年第6期140-142,共3页 Journal of Wuhan University of Technology
关键词 隐私保护数据挖掘 贝叶斯网络 评价函数 privacy-preserving data mining bayesian networks score function
分类号 TP309 [自动化与计算机技术—计算机系统结构]
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参考文献8

  • 1张鹏,童云海,唐世渭,杨冬青,马秀莉.一种有效的隐私保护关联规则挖掘方法[J].软件学报,2006,17(8):1764-1774. 被引量：53
  • 2Jaideep V, Chris C. Privacy Preserving Association Rule Mining in Vertically Partitioned Data[A]. In Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery in Databases and Data Mining[ C]. Edmonton:ACM Press, 2002 : 639-644.
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二级参考文献14

  • 1Verykios VS,Bertino E,Fovino IN,Provenza LP,Saygin Y,Theodoridis Y.State-of-the-Art in privacy preserving data mining.SIGMOD Record,2004,33(1):50-57.
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  • 3Agrawal R,Srikant R.Privacy-Preserving data mining.In:Weidong C,Jeffrey F,eds.Proc.of the ACM SIGMOD Conf.on Management of Data.Dallas:ACM Press,2000.439-450.
  • 4Rizvi SJ,Haritsa JR.Maintaining data privacy in association rule mining.In:Bernstein PA,Ioannidis YE,Ramakrishnan R,Papadias D,eds.Proc.of the 28th Int'l Conf.on Very Large Data Bases.Hong Kong:Morgan Kaufmann Publishers,2002.682-693.
  • 5Agrawal S,Krishnan V,Haritsa JR.On addressing efficiency concerns in privacy-preserving mining.In:Lee YJ,Li JZ,Whang KY,Lee D,eds.Proc.of the 9th Int'l Conf.on Database Systems for Advanced Applications.LNCS 2973,Jeju Island:Springer-Verlag,2004.113-124.
  • 6Evfimievski A.Randomization in privacy preserving data mining.SIGKDD Explorations,2002,4(2):43-48.
  • 7Evfimievski A,Srikant R,Agrawal R,Gehrke J.Privacy preserving mining of association rules.In:Hand D,Keim D,Ng R,eds.Proc.of the 8th ACM SIGKDD Int'l Conf.on Knowledge Discovery and Data Mining.Edmonton:ACM Press,2002.217-228.
  • 8Saygin Y,Verykios VS,Clifton C.Using unknowns to prevent discovery of association rules.ACM SIGMOD Record,2001,30(4):45-54.
  • 9Oliveira SRM,Zaiane OR.Privacy preserving frequent itemset mining.In:Clifton C,EstivillCastro V,eds.Proc.of the IEEE Int'l Conf.on Data Mining Workshop on Privacy,Security and Data Mining.Maebashi:IEEE Computer Society,2002.43-54.
  • 10Kantarcioglu M,Clifton C.Privacy-Preserving distributed mining of association rules on horizontally partitioned data.IEEE Trans.on Knowledge and Data Engineering,2004,16(9):1026-1037.

共引文献52

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二级引证文献2

武汉理工大学学报
2008年 第6期

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