Using the Complex Measure in an Assessment of the Information Loss Due to the Microdata Disclosure Control

Andrzej Młodak
{"title":"Using the Complex Measure in an Assessment of the Information Loss Due to the Microdata Disclosure Control","authors":"Andrzej Młodak","doi":"10.5604/01.3001.0013.8285","DOIUrl":null,"url":null,"abstract":"The paper contains a proposal of original method of assessment of information loss resulted from an application of the Statistical Disclosure Control (SDC) conducted during preparation of the resulting data to the publication and disclosure to interested users. The SDC tools enable protection of sensitive data from their disclosure – both direct and indirect. The article focuses on pseudonimised microdata, i.e. individual data without fundamental identifiers, used for scientific purposes. This control is usually to suppress, swapping or disturbing of original data. However, such intervention is connected with the loss of some information. Optimization of choice of relevant SDC method requires then a minimization of such loss (and risk of disclosure of protected data). Traditionally used methods of measurement of such loss are not rarely sensitive to dissimilarities resulting from scale and scope of values of variables and cannot be used for ordinal data. Many of them weakly take also connections between variables into account, what can be important in various analyses. Hence, this paper is aimed at presentation of a proposal (having the source in papers by Zdzisław Hellwig) concerning use of a method of normalized and easy interpretable complex measure (called also the synthetic indicator) for connected features based on benchmark and anti–benchmark of development to the assessment of information loss resulted from an application of some SDC techniques and at studying its practical utility. The measure is here constructed on the basis of distances between original data and data after application of the SDC taking measurement scales into account.","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Przegląd Statystyczny","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5604/01.3001.0013.8285","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The paper contains a proposal of original method of assessment of information loss resulted from an application of the Statistical Disclosure Control (SDC) conducted during preparation of the resulting data to the publication and disclosure to interested users. The SDC tools enable protection of sensitive data from their disclosure – both direct and indirect. The article focuses on pseudonimised microdata, i.e. individual data without fundamental identifiers, used for scientific purposes. This control is usually to suppress, swapping or disturbing of original data. However, such intervention is connected with the loss of some information. Optimization of choice of relevant SDC method requires then a minimization of such loss (and risk of disclosure of protected data). Traditionally used methods of measurement of such loss are not rarely sensitive to dissimilarities resulting from scale and scope of values of variables and cannot be used for ordinal data. Many of them weakly take also connections between variables into account, what can be important in various analyses. Hence, this paper is aimed at presentation of a proposal (having the source in papers by Zdzisław Hellwig) concerning use of a method of normalized and easy interpretable complex measure (called also the synthetic indicator) for connected features based on benchmark and anti–benchmark of development to the assessment of information loss resulted from an application of some SDC techniques and at studying its practical utility. The measure is here constructed on the basis of distances between original data and data after application of the SDC taking measurement scales into account.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于复杂测度的微数据披露控制信息损失评估
本文提出了一种评估因统计披露控制(SDC)而导致的信息损失的原始方法,该方法是在准备结果数据的发布和向感兴趣的用户披露过程中进行的。SDC工具可以保护敏感数据免受直接和间接的泄露。本文重点关注伪化微数据,即用于科学目的的没有基本标识符的个人数据。这种控制通常是为了抑制、交换或干扰原始数据。然而,这种干预与某些信息的丢失有关。优化相关SDC方法的选择需要将此类损失(以及受保护数据泄露的风险)最小化。传统上使用的测量这种损失的方法很少对变量值的规模和范围造成的差异敏感,不能用于有序数据。他们中的许多人也没有考虑到变量之间的联系,这在各种分析中可能很重要。因此,本文旨在提出一项建议(来源来自Zdzisław Hellwig的论文),该建议涉及使用基于基准和反基准开发的连接特征归一化且易于解释的复杂度量(也称为合成指标)方法来评估由于某些SDC技术的应用而导致的信息损失并研究其实际效用。这里的测度是基于SDC应用后的原始数据与考虑了测量尺度的数据之间的距离来构建的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Impact of a priori positive information on the results of voting methods Comparison of the accuracy of forecasts bsed on neural networks before and after the outbreak of the COVID-19 pandemic on the example of selected exchange rates Estimation of Yu and Meyer bivariate stochastic volatility model by iterated filtering Sample size in clinical trials – challenges and approaches Alternative investments during turbulent times comparison of dynamic relationship
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1