M. Ashouri-Talouki, Ahmad Baraani-Dastjerdi, N. Movahedinia
{"title":"盲定位:通过盲签名支持用户位置隐私","authors":"M. Ashouri-Talouki, Ahmad Baraani-Dastjerdi, N. Movahedinia","doi":"10.1109/ICCKE.2017.8167928","DOIUrl":null,"url":null,"abstract":"Location-based queries have brought challenging privacy issues for mobile users. Having access to data, anytime from anywhere, raises many security concerns. One of these concerns is user's location privacy, where a user must reveal her location to get the desired result. The question is how to benefit from such queries without endangering user's location privacy. This paper presents a new method called “BlindLocation”, to support users' location privacy during the use of location-based queries. In BlindLocation method, without a third trusted party, the user gets the desired service with a high quality while preserving her location privacy. In this method, the mobile database server receives a location-dependent query and a location object without any clue about the owner of this information. BlindLocation also provides a mechanism to anonymously authenticate the user, such that the mobile database cannot access to users' identities, while it can verify users' authorization. Consequently, location information is protected from the mobile databases, as well as malicious attackers. Extensive experiments show that the proposed protocol is efficient in terms of computation and communication costs. A security analysis shows the resistance of the protocol against collusion, disruption and background knowledge attacks in a malicious model.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"BlindLocation: Supporting user location privacy using blind signature\",\"authors\":\"M. Ashouri-Talouki, Ahmad Baraani-Dastjerdi, N. Movahedinia\",\"doi\":\"10.1109/ICCKE.2017.8167928\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Location-based queries have brought challenging privacy issues for mobile users. Having access to data, anytime from anywhere, raises many security concerns. One of these concerns is user's location privacy, where a user must reveal her location to get the desired result. The question is how to benefit from such queries without endangering user's location privacy. This paper presents a new method called “BlindLocation”, to support users' location privacy during the use of location-based queries. In BlindLocation method, without a third trusted party, the user gets the desired service with a high quality while preserving her location privacy. In this method, the mobile database server receives a location-dependent query and a location object without any clue about the owner of this information. BlindLocation also provides a mechanism to anonymously authenticate the user, such that the mobile database cannot access to users' identities, while it can verify users' authorization. Consequently, location information is protected from the mobile databases, as well as malicious attackers. Extensive experiments show that the proposed protocol is efficient in terms of computation and communication costs. A security analysis shows the resistance of the protocol against collusion, disruption and background knowledge attacks in a malicious model.\",\"PeriodicalId\":151934,\"journal\":{\"name\":\"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCKE.2017.8167928\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCKE.2017.8167928","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
BlindLocation: Supporting user location privacy using blind signature
Location-based queries have brought challenging privacy issues for mobile users. Having access to data, anytime from anywhere, raises many security concerns. One of these concerns is user's location privacy, where a user must reveal her location to get the desired result. The question is how to benefit from such queries without endangering user's location privacy. This paper presents a new method called “BlindLocation”, to support users' location privacy during the use of location-based queries. In BlindLocation method, without a third trusted party, the user gets the desired service with a high quality while preserving her location privacy. In this method, the mobile database server receives a location-dependent query and a location object without any clue about the owner of this information. BlindLocation also provides a mechanism to anonymously authenticate the user, such that the mobile database cannot access to users' identities, while it can verify users' authorization. Consequently, location information is protected from the mobile databases, as well as malicious attackers. Extensive experiments show that the proposed protocol is efficient in terms of computation and communication costs. A security analysis shows the resistance of the protocol against collusion, disruption and background knowledge attacks in a malicious model.