New Data Publishing Framework in the Big Data Environments

Jun Yang, Zheli Liu, Chunfu Jia, Kai Lin, Zijing Cheng
{"title":"New Data Publishing Framework in the Big Data Environments","authors":"Jun Yang, Zheli Liu, Chunfu Jia, Kai Lin, Zijing Cheng","doi":"10.1109/3PGCIC.2014.139","DOIUrl":null,"url":null,"abstract":"The traditional data publishing methods will remove the sensitive attributes and generate the abundant records to achieve the goal of privacy protection. In the big data environment, they cannot satisfy some data mining tasks with privacy considerations. This paper provides a new data publishing framework. It can preserve the data integrity, i.e., the original data structure is preserved, and it doesn't require deleting any attribute and adding k-times data to achieve anonymity.","PeriodicalId":395610,"journal":{"name":"2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3PGCIC.2014.139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

The traditional data publishing methods will remove the sensitive attributes and generate the abundant records to achieve the goal of privacy protection. In the big data environment, they cannot satisfy some data mining tasks with privacy considerations. This paper provides a new data publishing framework. It can preserve the data integrity, i.e., the original data structure is preserved, and it doesn't require deleting any attribute and adding k-times data to achieve anonymity.
大数据环境下的新数据发布框架
传统的数据发布方法会去除敏感属性,生成丰富的记录,从而达到保护隐私的目的。在大数据环境下,由于隐私方面的考虑,它们无法满足一些数据挖掘任务。本文提供了一个新的数据发布框架。它可以保持数据的完整性,即保留原有的数据结构,并且不需要删除任何属性和添加k次数据来实现匿名。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信