{"title":"用于增强web认证的设备指纹识别:方法的分类和分析","authors":"Furkan Alaca, P. V. Oorschot","doi":"10.1145/2991079.2991091","DOIUrl":null,"url":null,"abstract":"Device fingerprinting is commonly used for tracking users. We explore device fingerprinting but in the specific context of use for augmenting authentication, providing a state-of-the-art view and analysis. We summarize and classify 29 available methods and their properties; define attack models relevant to augmenting passwords for user authentication; and qualitatively compare them based on stability, repeatability, resource use, client passiveness, difficulty of spoofing, and distinguishability offered.","PeriodicalId":419419,"journal":{"name":"Proceedings of the 32nd Annual Conference on Computer Security Applications","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"87","resultStr":"{\"title\":\"Device fingerprinting for augmenting web authentication: classification and analysis of methods\",\"authors\":\"Furkan Alaca, P. V. Oorschot\",\"doi\":\"10.1145/2991079.2991091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Device fingerprinting is commonly used for tracking users. We explore device fingerprinting but in the specific context of use for augmenting authentication, providing a state-of-the-art view and analysis. We summarize and classify 29 available methods and their properties; define attack models relevant to augmenting passwords for user authentication; and qualitatively compare them based on stability, repeatability, resource use, client passiveness, difficulty of spoofing, and distinguishability offered.\",\"PeriodicalId\":419419,\"journal\":{\"name\":\"Proceedings of the 32nd Annual Conference on Computer Security Applications\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"87\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 32nd Annual Conference on Computer Security Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2991079.2991091\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 32nd Annual Conference on Computer Security Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2991079.2991091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Device fingerprinting for augmenting web authentication: classification and analysis of methods
Device fingerprinting is commonly used for tracking users. We explore device fingerprinting but in the specific context of use for augmenting authentication, providing a state-of-the-art view and analysis. We summarize and classify 29 available methods and their properties; define attack models relevant to augmenting passwords for user authentication; and qualitatively compare them based on stability, repeatability, resource use, client passiveness, difficulty of spoofing, and distinguishability offered.