{"title":"了解Android图形密码模式的可用性和安全性的视觉感知","authors":"Adam J. Aviv, Dane Fichter","doi":"10.1145/2664243.2664253","DOIUrl":null,"url":null,"abstract":"This paper reports the results of a user study of the Android graphical password system using an alternative survey methodology, pairwise preferences, that requests participants to select between pairs of patterns indicating either a security or usability preference. By carefully selecting password pairs to isolate a visual feature, a visual perception of usability and security of different features can be measured. We conducted a large IRB-approved survey using pairwise preferences which attracted 384 participants on Amazon Mechanical Turk. Analyzing the results, we find that visual features that can be attributed to complexity indicated a stronger perception of security, while spatial features, such as shifts up/down or left/right are not strong indicators for security or usability. We extended and applied the survey data by building logistic models to predict perception preferences by training on features used in the survey and other features proposed in related work. The logistic model accurately predicted preferences above 70%, twice the rate of random guessing, and the strongest feature in classification is password distance, the total length of all lines in the pattern, a feature not used in the online survey. This result provides insight into the internal visual calculus of users when comparing choices and selecting visual passwords, and the ultimate goal of this work is to leverage the visual calculus to design systems where inherent perceptions for usability coincides with a known metric of security.","PeriodicalId":104443,"journal":{"name":"Proceedings of the 30th Annual Computer Security Applications Conference","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"Understanding visual perceptions of usability and security of Android's graphical password pattern\",\"authors\":\"Adam J. Aviv, Dane Fichter\",\"doi\":\"10.1145/2664243.2664253\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper reports the results of a user study of the Android graphical password system using an alternative survey methodology, pairwise preferences, that requests participants to select between pairs of patterns indicating either a security or usability preference. By carefully selecting password pairs to isolate a visual feature, a visual perception of usability and security of different features can be measured. We conducted a large IRB-approved survey using pairwise preferences which attracted 384 participants on Amazon Mechanical Turk. Analyzing the results, we find that visual features that can be attributed to complexity indicated a stronger perception of security, while spatial features, such as shifts up/down or left/right are not strong indicators for security or usability. We extended and applied the survey data by building logistic models to predict perception preferences by training on features used in the survey and other features proposed in related work. The logistic model accurately predicted preferences above 70%, twice the rate of random guessing, and the strongest feature in classification is password distance, the total length of all lines in the pattern, a feature not used in the online survey. This result provides insight into the internal visual calculus of users when comparing choices and selecting visual passwords, and the ultimate goal of this work is to leverage the visual calculus to design systems where inherent perceptions for usability coincides with a known metric of security.\",\"PeriodicalId\":104443,\"journal\":{\"name\":\"Proceedings of the 30th Annual Computer Security Applications Conference\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 30th Annual Computer Security Applications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2664243.2664253\",\"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 30th Annual Computer Security Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2664243.2664253","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Understanding visual perceptions of usability and security of Android's graphical password pattern
This paper reports the results of a user study of the Android graphical password system using an alternative survey methodology, pairwise preferences, that requests participants to select between pairs of patterns indicating either a security or usability preference. By carefully selecting password pairs to isolate a visual feature, a visual perception of usability and security of different features can be measured. We conducted a large IRB-approved survey using pairwise preferences which attracted 384 participants on Amazon Mechanical Turk. Analyzing the results, we find that visual features that can be attributed to complexity indicated a stronger perception of security, while spatial features, such as shifts up/down or left/right are not strong indicators for security or usability. We extended and applied the survey data by building logistic models to predict perception preferences by training on features used in the survey and other features proposed in related work. The logistic model accurately predicted preferences above 70%, twice the rate of random guessing, and the strongest feature in classification is password distance, the total length of all lines in the pattern, a feature not used in the online survey. This result provides insight into the internal visual calculus of users when comparing choices and selecting visual passwords, and the ultimate goal of this work is to leverage the visual calculus to design systems where inherent perceptions for usability coincides with a known metric of security.