Active user authentication for smartphones: A challenge data set and benchmark results
Active user authentication for smartphones: A challenge data set and benchmark results
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DOI：
10.1109/btas.2016.7791155
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发表时间：
2016-09
期刊：
影响因子：
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通讯作者：
U. Mahbub;Sayantan Sarkar;Vishal M. Patel;R. Chellappa
中科院分区：
文献类型：
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作者：
U. Mahbub;Sayantan Sarkar;Vishal M. Patel;R. Chellappa
在本文中，智能手机的自动用户验证技术进行了研究。介绍了一个独特的非商业数据集，马里兰州大学主动认证数据集02（UMDAA-02）的多模态用户认证研究。本文重点介绍了三种传感器-前置摄像头，触摸传感器和位置服务，同时对其他模式进行了一般描述。人脸检测，人脸验证，基于触摸的用户识别和基于位置的下一个地方预测的基准测试结果，这表明，更强大的方法微调到移动的平台，需要达到令人满意的验证精度。该数据集将提供给研究界，以促进更多的研究。
In this paper, automated user verification techniques for smartphones are investigated. A unique non-commercial dataset, the University of Maryland Active Authentication Dataset 02 (UMDAA-02) for multi-modal user authentication research is introduced. This paper focuses on three sensors - front camera, touch sensor and location service while providing a general description for other modalities. Benchmark results for face detection, face verification, touch-based user identification and location-based next-place prediction are presented, which indicate that more robust methods fine-tuned to the mobile platform are needed to achieve satisfactory verification accuracy. The dataset will be made available to the research community for promoting additional research.