刘英华, 刘永彬, 李广原, 郭建威. 一种增强的个性化匿名隐私保护模型[J]. 微电子学与计算机, 2011, 28(8): 4-8.
引用本文: 刘英华, 刘永彬, 李广原, 郭建威. 一种增强的个性化匿名隐私保护模型[J]. 微电子学与计算机, 2011, 28(8): 4-8.
LIU Ying-hua, LIU Yong-bin, LI Guang-yuan, GUO Jian-wei. An Enhanced Personalized Privacy Preserving k-anonymity Model[J]. Microelectronics & Computer, 2011, 28(8): 4-8.
Citation: LIU Ying-hua, LIU Yong-bin, LI Guang-yuan, GUO Jian-wei. An Enhanced Personalized Privacy Preserving k-anonymity Model[J]. Microelectronics & Computer, 2011, 28(8): 4-8.

一种增强的个性化匿名隐私保护模型

An Enhanced Personalized Privacy Preserving k-anonymity Model

  • 摘要: 匿名模型是近年来隐私保护研究的热点技术之一,主要研究如何在数据发布中避免敏感数据的泄露,又能保证数据发布的高效用性.提出了一种个性化(αs,l)-多样k-匿名模型,该方法将敏感属性泛化成泛化树,根据数据发布中隐私保护的具体要求,给各结点设置不同的α约束,发布符合个性化匿名模型的数据.该方法在保护隐私的同时进一步提高信息的个性化要求.实验结果表明,该方法提高了信息的有效性,具有很高的实用性.

     

    Abstract: Recently,anonymization model is one of the hot topic techniques in privacy preserving research.The mainly research is how to avoid leakage of sensitive data in data publishing,but also ensures the efficient use of data.This paper proposed a personalized(αs,l)-diversity k-anonymity model.This method publish the personalized data though generalization technology and α restriction for different code of the generalization tree.This method reserves more information while maintaining the individual privacy.The model are evaluated in an experimental scenario,reserving more information and demonstrating practical applicability of the approaches.

     

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