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首页> 外文期刊>Neural computing & applications >Machine learning algorithms for improving security on touch screen devices: a survey, challenges and new perspectives
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Machine learning algorithms for improving security on touch screen devices: a survey, challenges and new perspectives

机译：用于改进触摸屏设备的安全性的机器学习算法：调查，挑战和新观点

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摘要

Mobile phone touch screen devices are equipped with high processing power and high memory. This led to users not only storing photos or videos but stored sensitive application such as banking applications. As a result of that the security system of the mobile phone touch screen devices becomes sacrosanct. The application of machine learning algorithms in enhancing security on mobile phone touch screen devices is gaining a tremendous popularity in both academia and the industry. However, notwithstanding the growing popularity, up to date no comprehensive survey has been conducted on machine learning algorithms solutions to improve the security of mobile phone touch screen devices. This survey aims to connect this gap by conducting a comprehensive survey on the solutions of machine learning algorithms to improve the security of mobile phone touch screen devices including the analysis and synthesis of the algorithms and methodologies provided for those solutions. This article presents a comprehensive survey and a new taxonomy of the state-of-the-art literature on machine learning algorithms in improving the security of mobile phone touch screen devices. The limitation of the methodology in each article reviewed is pointed out. Challenges of the existing approaches and new perspective of future research directions for developing more accurate and robust solutions to mobile phone touch screen security are discussed. In particular, the survey found that exploring of different aspects of deep learning solutions to improve the security of mobile phone touch screen devices is under-explored.
机译：手机触摸屏设备配有高处理电量和高内存。这导致用户不仅存储照片或视频，而是存储敏感的应用程序，如银行应用程序。由于移动电话触摸屏设备的安全系统成为SACROSANCT。机器学习算法在增强手机触摸屏设备上的应用中的应用是在学术界和行业中获得巨大的普及。然而，尽管越来越受欢迎，但在机器学习算法解决方案上没有进行全面的调查，以改善手机触摸屏设备的安全性。该调查旨在通过对机器学习算法的解决方案进行全面的调查来改善移动电话触摸屏设备的安全性，包括分析和合成这些解决方案的分析和综合来联系这种差距。本文提出了在提高手机触摸屏设备的安全性的机器学习算法上进行了全面的调查和新的文献新分类。审查的每篇文章中的方法的限制被指出。讨论了对移动电话触摸屏安全更加准确和强大的解决方案的未来研究方向的现有方法和新视角的挑战。特别是，调查发现，探讨了探索深度学习解决方案的不同方面，以改善移动电话触摸屏设备的安全性。

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