{"title":"支持比较的保护隐私的映射方案","authors":"Qiang Tang","doi":"10.1145/1866835.1866846","DOIUrl":null,"url":null,"abstract":"To cater to the privacy requirements in cloud computing, we introduce a new primitive, namely Privacy Preserving Mapping (PPM) schemes supporting comparison. An PPM scheme enables a user to map data items into images in such a way that, with a set of images, any entity can determine the <, =, > relationships among the corresponding data items. We propose three privacy notions, namely ideal privacy, level-1 privacy, and level-2 privacy, and three constructions satisfying these privacy notions respectively.","PeriodicalId":300613,"journal":{"name":"Cloud Computing Security Workshop","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Privacy preserving mapping schemes supporting comparison\",\"authors\":\"Qiang Tang\",\"doi\":\"10.1145/1866835.1866846\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To cater to the privacy requirements in cloud computing, we introduce a new primitive, namely Privacy Preserving Mapping (PPM) schemes supporting comparison. An PPM scheme enables a user to map data items into images in such a way that, with a set of images, any entity can determine the <, =, > relationships among the corresponding data items. We propose three privacy notions, namely ideal privacy, level-1 privacy, and level-2 privacy, and three constructions satisfying these privacy notions respectively.\",\"PeriodicalId\":300613,\"journal\":{\"name\":\"Cloud Computing Security Workshop\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cloud Computing Security Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1866835.1866846\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cloud Computing Security Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1866835.1866846","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
To cater to the privacy requirements in cloud computing, we introduce a new primitive, namely Privacy Preserving Mapping (PPM) schemes supporting comparison. An PPM scheme enables a user to map data items into images in such a way that, with a set of images, any entity can determine the <, =, > relationships among the corresponding data items. We propose three privacy notions, namely ideal privacy, level-1 privacy, and level-2 privacy, and three constructions satisfying these privacy notions respectively.
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