Currently, smartphone security has received much more attention as users may use their devices to perform various sensitive tasks. For example, users can utilize mobile banking applications for online shopping, which may store many sensitive data on their devices. Hence there is a need to authenticate users and detect imposters. However, traditional textual passwords are easily compromised and are not convenient for users to remember for a long time due to long-term memory limitation. To complement textual passwords, behavioral authentication is developed by authenticating a user based on the relevant biometric features. In this work, we focus on simple shape-based behavioral authentication that requires users to draw shape(s) for authentication, and investigate how to design such kind of behavioral authentication in practice. We consider two research questions: (1) whether the authentication accuracy varies with different shapes, and (2) how many shapes can be used to achieve good usability. In the evaluation, we perform two user studies with 60 participants and measure some typical supervised learning classifiers. Based on the results, we provide insights on designing a supervised shape-based behavioral authentication system, as compared with similar schemes.

当前，智能手机的安全性受到了越来越多的关注，因为用户可以使用其设备执行各种敏感任务。例如，用户可以利用移动银行应用程序进行在线购物，该应用程序可以在其设备上存储许多敏感数据。因此，需要认证用户并检测冒名顶替者。但是，由于长期的存储限制，传统的文本密码很容易遭到破坏，并且长时间不方便用户记住。为了补充文本密码，通过基于相关生物特征对用户进行身份验证来开发行为身份验证。在这项工作中，我们专注于简单的基于形状的行为身份验证，该行为要求用户绘制形状进行身份验证，并研究如何在实践中设计这种行为身份验证。我们考虑两个研究问题：（1）身份验证的准确性是否随形状不同而变化；（2）可以使用多少个形状来实现良好的可用性。在评估中，我们与60名参与者进行了两次用户研究，并评估了一些典型的监督学习分类器。根据结果​​，与类似方案相比，我们提供了有关设计基于形状的监督行为认证系统的见解。