Body-Taps: Authenticating Your Device Through Few Simple Taps
Body-Taps: Authenticating Your Device Through Few Simple Taps
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DOI：
10.1109/btas.2018.8698602
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发表时间：
2018-10
期刊：
影响因子：
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通讯作者：
Diksha Shukla;Guangcheng Wei;Donghua Xue;Zhanpeng Jin;V. Phoha
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作者：
Diksha Shukla;Guangcheng Wei;Donghua Xue;Zhanpeng Jin;V. Phoha
为了满足日益增长的需求上的认证方法的智能移动的和可穿戴设备具有小的形状因子和受限的屏幕显示，我们引入了一种新的认证机制，身体轻敲，认证设备的基础上的轻敲代码手势的形式，通过内置的运动传感器捕获。Body-Taps要求用户通过在他或她自己身体上的设定锚点上敲击设备，将TapCode设置为设备的解锁代码。目标设备基于两个标准进行认证：（1）用户对设置的Tap-Code的了解，以及（2）通过智能设备的内置运动传感器（加速度计和陀螺仪）测量的BodyTap手势。我们的实验表明，建议的Body-Taps系统可以实现平均认证准确率超过99.5%的数据集，包括230 Body-Tap样本从23个科目，使用随机森林（RF），神经网络（NNet），和线性判别分析（LDA）分类。我们的工作产生一个重量轻，成本低，易于使用的安全认证系统，需要最少的努力，并提供令人满意的可用性。
To fulfill the increasing demands on authentication methods on the smart mobile and wearable devices with small form factors and constrained screen displays, we introduce a novel authentication mechanism, Body-Taps, which authenticates a device based on the Tap-Code gestures in the form of hand movements captured through the built-in motion sensors. The Body-Taps require a user to set a TapCode as an unlock code for the device by tapping the device on the set anchor points on his or her own body. The target device is authenticated based on two criterion: (1) the user’s knowledge of the set Tap-Code, and (2) the BodyTap gestures measured through the smart device’s built-in motion sensors (accelerometer and gyroscope). Our experiments show that the proposed Body-Taps system can achieve an average authentication accuracy over 99.5% on a dataset comprising of 230 Body-Tap samples from 23 subjects, using Random Forest (RF), Neural Network (NNet), and Linear Discriminant Analysis (LDA) classifiers. Our work yields a light-weight, low-cost, and easy-to-use secure authentication system that requires minimal efforts and offers satisfactory usability.