Continuous authentication of smartphone users by fusing typing, swiping, and phone movement patterns

Continuous authentication of smartphone users by fusing typing, swiping, and phone movement patterns
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通过融合打字、滑动和手机移动模式对智能手机用户进行持续身份验证

DOI:
10.1109/btas.2016.7791164
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发表时间:
2016
期刊:
2016 IEEE 8th International Conference on
影响因子:
--
通讯作者:
Serwadda, Abdul
Serwadda, Abdul
中科院分区:
--
文献类型:
--
作者:
Kumar, Rajesh;Phoha, Vir V.;Serwadda, Abdul

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我们研究了三种生物特征认证方式的融合,即滑动手势,打字模式和打字或滑动过程中观察到的手机移动模式。定制了一个网络浏览器,以便在不受约束的环境中收集4至7天内从上述模式产生的数据。对每种模态采用滑动窗口机制提取多个特征,并利用信息增益、相关性和对称不确定性进行分析。最后,来自连续滑动窗口的五个特征,来自连续键入字母窗口的三十个特征,以及来自滑动/键入时相应的手机移动模式的九个特征被用于构建认证系统。我们评估了28个用户的数据集上的每种模态及其融合的性能。刷卡和相应的手机移动模式的特征级融合实现了93.33%的认证准确率,而打字行为和相应的手机移动模式的分数级融合实现了89.31%的认证准确率。
We studied the fusion of three biometric authentication modalities, namely, swiping gestures, typing patterns and the phone movement patterns observed during typing or swiping. A web browser was customized to collect the data generated from the aforementioned modalities over four to seven days in an unconstrained environment. Several features were extracted by using sliding window mechanism for each modality and analyzed by using information gain, correlation, and symmetric uncertainty. Finally, five features from windows of continuous swipes, thirty features from windows of continuously typed letters, and nine features from corresponding phone movement patterns while swiping/typing were used to build the authentication system. We evaluated the performance of each modality and their fusion over a dataset of 28 users. The feature-level fusion of swiping and the corresponding phone movement patterns achieved an authentication accuracy of 93.33%, whereas, the score-level fusion of typing behaviors and the corresponding phone movement patterns achieved an authentication accuracy of 89.31 %.
DOI: 10.1145/2516960
发表时间: 2013-09
期刊: ACM Trans. Inf. Syst. Secur.
影响因子: --
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