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计算机工程

• 安全技术 • 上一篇    下一篇

一种保护私有信息的空间离群点检测方法

俞庆英a,b,罗永龙a,b,陈付龙a,郑孝遥a,b   

  1. (安徽师范大学 a.数学计算机科学学院;b.国土资源与旅游学院,安徽 芜湖 241003)
  • 收稿日期:2016-06-06 出版日期:2017-03-15 发布日期:2017-03-15
  • 作者简介:俞庆英(1980—),女,讲师、博士研究生,主研方向为信息安全、空间数据处理;罗永龙,教授、博士、博士生导师;陈付龙,教授、博士;郑孝遥,副教授、博士研究生。
  • 基金资助:
    国家自然科学基金(61370050,61572036);安徽省自然科学基金(1508085QF134);安徽师范大学创新基金(2016XJJ074,2015cxjj11)。

A Privacy-preserving Spatial Outlier Detection Method

YU Qingying  a,b,LUO Yonglong  a,b,CHEN Fulong  a,ZHENG Xiaoyao  a,b   

  1. (a.School of Mathematics and Computer Science; b.School of Territorial Resources and Tourism,Anhui Normal University,Wuhu,Anhui 241003,China)
  • Received:2016-06-06 Online:2017-03-15 Published:2017-03-15

摘要:

针对现有空间离群点检测方法难以同时保证数据安全性和检测结果有效性的问题,提出一种隐私保护的空间离群点检测方法。该方法基于空间邻域行为属性值的统计结果及马哈拉诺比斯距离进行空间离群点的检测,通过对基于半诚实模型的安全多方距离、合并向量的中位数及标准化等计算协议的定义和应用,实现私有信息的保护。实验结果表明,该方法在保护隐私信息的同时保证了检测结果的准确性。

关键词: 空间离群点检测, 空间邻域, 空间属性, 非空间属性, 安全多方计算

Abstract: Foucusing on the issue that the existing spatial outlier detection methods fail to effectively solve the problem of guaranteeing both the data security and the validity of detection results at the same time,a privacy-preserving spatial outlier detection method is proposed,which uses statistical results of behavior attributes in spatial neighborhood and Mahalanobis distance to detect spatial outliers,and protects the privacy information by using the secure multi-party computation protocol based on semi-honest model,including secure distance computation,secure median computation of the combined vector and secure standardization protocols.Experimental results show that the method guarantees both the ability of privacy preserving and the effect of spatial outlier detection.

Key words: spatial outlier detection, spatial neighborhood, spatial attribute, non-spatial attribute, Secure Multi-party Computation(SMC)

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