Smartphone Security Using Swipe Behavior-based Authentication
Smartphone Security Using Swipe Behavior-based Authentication
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DOI：
10.32604/iasc.2021.015913
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发表时间：
2021
影响因子：
2
通讯作者：
Adnan Bin Amanat Ali;V. Ponnusamy;A. Sangodiah;Roobaea Alroobaea;Noor Zaman Jhanjhi;Uttam Ghosh;Mehedi Masud
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文献类型：
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作者：
Adnan Bin Amanat Ali;V. Ponnusamy;A. Sangodiah;Roobaea Alroobaea;Noor Zaman Jhanjhi;Uttam Ghosh;Mehedi Masud
大多数智能手机用户更喜欢简单方便的身份验证，而不需要记住复杂的密码或绘制复杂的图案。优选地，在一次性认证之后，不存在对用户真实性的验证。因此，针对未经授权用户的安全和隐私保护是一个重要的研究领域。行为认证是一种新兴的安全技术，因其唯一性和透明性而受到人们的关注。本文构建了一种基于行为的身份认证系统，通过滑动动作对用户进行一次性传统身份认证后的持续身份认证。关键功能是为滑动移动选择最佳功能集。使用了五个机器学习分类器，其中随机森林是根据准确率和F-度量值的最佳值来选择的。通过将所有计算能力转移到云服务器来克服智能手机的计算限制，开发了一个实时系统。该系统在三部智能手机上进行了测试，结果发现，至少七次滑动就足以检查用户的真实性。在我们的实验中，提出的特征集比最新的特征集表现得更好。
Most smartphone users prefer easy and convenient authentication without remembering complicated passwords or drawing intricate patterns. Preferably, after one-time authentication, there is no verification of the user’s authenticity. Therefore, security and privacy against unauthorized users is a crucial research area. Behavioral authentication is an emerging security technique that is gaining attention for its uniqueness and transparency. In this paper, a behavior-based authentication system is built using swipe movements to continuously authenticate the user after one-time traditional authentication. The key feature is the selection of an optimal feature set for the swipe movement. Five machine learning classifiers are used, of which random forest is selected based on the best values of accuracy and F-measure. A real-time system is developed by shifting all of the computational power to a cloud server to overcome the smartphone’s computational limitations. The system is tested on three smartphones, and it is found that a minimum of seven swipes is sufficient to check user authenticity. In our experiments, the proposed feature set performs better than a state-of-the-art feature set.