An empirical test of household identification risk in geomasked maps     

Dara E. Seidl  Piotr Jankowski  Atsushi Nara 《制图学和地理信息科学》2013,40(6):475-488

ABSTRACT

Geomasking techniques displace point data to new locations in order to protect privacy while maintaining overall spatial distributions. If the end users of geomasked data are unaware that the data are masked, there is a risk that they will incorrectly associate individuals at the new locations with the masked data attributes. The probability of correct and false household identification depends on human understanding of whether maps contain masked coordinates and the spatial relationships of the points to contextual geographic data. Using a map-based experiment, this study finds that confidence in performing a household identification is substantially lowered when masked points are situated equidistantly between residential parcels. Despite initial notifications that data are masked, map users often report confidence in assigning masked points to specific households. Only map users who receive frequent notifications that the points are masked have reduced confidence in associating them with particular households, thereby lowering identification risk.  相似文献   

基于灰关联的k匿名数据流隐私保护算法     

张岐山  郭昆 《东北石油大学学报》2012,(6):93-100,12

与静态数据不同,数据流具有潜在无限、快速到达、变化频繁等特点,使得数据流隐私保护面临问题.在保证匿名要求的前提下,从降低信息损失和节约计算时间角度,提出一种基于灰关联的数据流隐私保护匿名算法(DSAoGRA),采用灰色关联度描述元组间的相似度,将元组划分成k匿名簇,实现数据流的k匿名化.数据实验结果表明,该算法在满足匿名要求的同时,比CASTLE算法具有较低的信息损失和较少的计算时间.  相似文献