{"title":"Probabilistic privacy analysis of published views","authors":"Wendy Hui Wang, L. Lakshmanan","doi":"10.1145/1179601.1179616","DOIUrl":null,"url":null,"abstract":"Among techniques for ensuring privacy in data publishing, k-anonymity and publishing of views on private data are quite popular. In this paper, we consider data publishing by views and develop a probability framework for the analysis of privacy breach. We propose two attack models and derive the probability of privacy breach for each model.","PeriodicalId":74537,"journal":{"name":"Proceedings of the ACM Workshop on Privacy in the Electronic Society. ACM Workshop on Privacy in the Electronic Society","volume":"46 1","pages":"81-84"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ACM Workshop on Privacy in the Electronic Society. ACM Workshop on Privacy in the Electronic Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1179601.1179616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Among techniques for ensuring privacy in data publishing, k-anonymity and publishing of views on private data are quite popular. In this paper, we consider data publishing by views and develop a probability framework for the analysis of privacy breach. We propose two attack models and derive the probability of privacy breach for each model.
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