{"title":"递归分区和汇总:一种用于差异私有数据发布的实用框架","authors":"Wahbeh H. Qardaji, Ninghui Li","doi":"10.1145/2414456.2414477","DOIUrl":null,"url":null,"abstract":"In this paper we consider the problem of differentially private data publishing. In particular, we consider the scenario in which a trusted curator gathers sensitive information from a large number of respondents, creates a relational dataset where each tuple corresponds to one entity, such as an individual, a household, or an organization, and then publishes a privacy-preserving (i.e., sanitized or anonymized) version of the dataset. This has been referred to as the \"non-interactive\" mode of private data analysis, as opposed to the \"interactive\" mode, where the data curator provides an interface through which users may pose queries about the data, and get (possibly noisy) answers.","PeriodicalId":72308,"journal":{"name":"Asia CCS '22 : proceedings of the 2022 ACM Asia Conference on Computer and Communications Security : May 30-June 3, 2022, Nagasaki, Japan. ACM Asia Conference on Computer and Communications Security (17th : 2022 : Nagasaki-shi, Japan ; ...","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Recursive partitioning and summarization: a practical framework for differentially private data publishing\",\"authors\":\"Wahbeh H. Qardaji, Ninghui Li\",\"doi\":\"10.1145/2414456.2414477\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we consider the problem of differentially private data publishing. In particular, we consider the scenario in which a trusted curator gathers sensitive information from a large number of respondents, creates a relational dataset where each tuple corresponds to one entity, such as an individual, a household, or an organization, and then publishes a privacy-preserving (i.e., sanitized or anonymized) version of the dataset. This has been referred to as the \\\"non-interactive\\\" mode of private data analysis, as opposed to the \\\"interactive\\\" mode, where the data curator provides an interface through which users may pose queries about the data, and get (possibly noisy) answers.\",\"PeriodicalId\":72308,\"journal\":{\"name\":\"Asia CCS '22 : proceedings of the 2022 ACM Asia Conference on Computer and Communications Security : May 30-June 3, 2022, Nagasaki, Japan. ACM Asia Conference on Computer and Communications Security (17th : 2022 : Nagasaki-shi, Japan ; ...\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asia CCS '22 : proceedings of the 2022 ACM Asia Conference on Computer and Communications Security : May 30-June 3, 2022, Nagasaki, Japan. ACM Asia Conference on Computer and Communications Security (17th : 2022 : Nagasaki-shi, Japan ; ...\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2414456.2414477\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asia CCS '22 : proceedings of the 2022 ACM Asia Conference on Computer and Communications Security : May 30-June 3, 2022, Nagasaki, Japan. ACM Asia Conference on Computer and Communications Security (17th : 2022 : Nagasaki-shi, Japan ; ...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2414456.2414477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recursive partitioning and summarization: a practical framework for differentially private data publishing
In this paper we consider the problem of differentially private data publishing. In particular, we consider the scenario in which a trusted curator gathers sensitive information from a large number of respondents, creates a relational dataset where each tuple corresponds to one entity, such as an individual, a household, or an organization, and then publishes a privacy-preserving (i.e., sanitized or anonymized) version of the dataset. This has been referred to as the "non-interactive" mode of private data analysis, as opposed to the "interactive" mode, where the data curator provides an interface through which users may pose queries about the data, and get (possibly noisy) answers.