Understanding visual perceptions of usability and security of Android's graphical password pattern
Understanding visual perceptions of usability and security of Android's graphical password pattern
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DOI：
10.1145/2664243.2664253
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发表时间：
2014-12
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影响因子：
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通讯作者：
Adam J. Aviv;Dane Fichter
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文献类型：
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作者：
Adam J. Aviv;Dane Fichter
本文报告了Android图形密码系统的用户研究的结果，使用另一种调查方法，成对的偏好，要求参与者选择对模式之间表示安全性或可用性偏好。通过仔细选择密码对以隔离视觉特征，可以测量不同特征的可用性和安全性的视觉感知。我们使用成对偏好进行了一项大型IRB批准的调查，吸引了Amazon Mechanical Turk上的384名参与者。分析结果，我们发现，可归因于复杂性的视觉特征表明了更强的安全感，而空间特征，如向上/向下或向左/向右移动并不是安全性或可用性的强指标。我们通过构建逻辑模型来扩展和应用调查数据，通过对调查中使用的特征和相关工作中提出的其他特征进行训练来预测感知偏好。逻辑模型准确地预测了70%以上的偏好，是随机猜测的两倍，分类中最强的特征是密码距离，即图案中所有线条的总长度，这是在线调查中没有使用的特征。这一结果提供了深入了解用户的内部视觉演算时，比较选择和选择视觉密码，这项工作的最终目标是利用视觉演算设计系统的固有感知的可用性符合一个已知的安全性指标。
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.