论文标题
探索用于行为生物识别验证的机器学习分类模型
Exploration of Machine Learning Classification Models Used for Behavioral Biometrics Authentication
论文作者
论文摘要
在过去的几十年中，移动设备的生产和增强。尽管这种增长已经显着发展了这些设备的能力，但它们的安全一直落后。移动设备能力和安全性之间发展的这种对比是公众危险的敏感信息的一个重大问题。继续在该领域的先前工作，这项研究确定了当前用于行为生物识别移动身份验证方案的关键机器学习算法，并旨在在与触摸动力学和电话运动一起使用时对这些算法进行全面审查。在整个本文中，将讨论未来工作的好处，限制和建议。
Mobile devices have been manufactured and enhanced at growing rates in the past decades. While this growth has significantly evolved the capability of these devices, their security has been falling behind. This contrast in development between capability and security of mobile devices is a significant problem with the sensitive information of the public at risk. Continuing the previous work in this field, this study identifies key Machine Learning algorithms currently being used for behavioral biometric mobile authentication schemes and aims to provide a comprehensive review of these algorithms when used with touch dynamics and phone movement. Throughout this paper the benefits, limitations, and recommendations for future work will be discussed.
