Y. Yuan, Jing Yang, Jianpei Zhang, S. Lan, Junwei Zhang
{"title":"Evolution of privacy-preserving data publishing","authors":"Y. Yuan, Jing Yang, Jianpei Zhang, S. Lan, Junwei Zhang","doi":"10.1109/ASID.2011.5967410","DOIUrl":null,"url":null,"abstract":"To achieve privacy protection better in data publishing, data must be sanitized before release. Research on protecting individual privacy and data confidentiality has received contributions from many fields. In order to grasp the development of privacy preserving data publishing, we discussed the evolution of this theme, focused on privacy mechanism, data utility and its metrics. The privacy mechanism, such as k-anonymity, l-diversity and t-closeness, provides formal safety guarantees and data utility preserve useful information while publishing data. Meantime, we discussed social network privacy and location based service. Finally, we made a conclusion with respect to privacy preserving data publishing, and given further research directions.","PeriodicalId":328792,"journal":{"name":"2011 IEEE International Conference on Anti-Counterfeiting, Security and Identification","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Anti-Counterfeiting, Security and Identification","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASID.2011.5967410","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
To achieve privacy protection better in data publishing, data must be sanitized before release. Research on protecting individual privacy and data confidentiality has received contributions from many fields. In order to grasp the development of privacy preserving data publishing, we discussed the evolution of this theme, focused on privacy mechanism, data utility and its metrics. The privacy mechanism, such as k-anonymity, l-diversity and t-closeness, provides formal safety guarantees and data utility preserve useful information while publishing data. Meantime, we discussed social network privacy and location based service. Finally, we made a conclusion with respect to privacy preserving data publishing, and given further research directions.