触摸事件和人类活动通过智能手机进行持续身份验证
Vincenzo Gattulli1, Donato Impedovo2, Giuseppe Pirlo2
1Dipartimento di Informatica, Università degli studi di Bari Aldo Moro, 70125, Bari, Italy. Vincenzo.Gattulli@Uniba.It.
Scientific reports
|June 29, 2023
概括
使用触摸事件和智能手机传感器的持续身份验证显著提高了智能手机的安全性. 这种方法利用机器学习,在文件滚动过程中实现高准确度的用户验证.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 人与计算机的交互
背景情况:
- 现代智能手机安全依赖于持续身份验证方法.
- 触摸事件和人类活动为机器学习提供了无声,丰富的数据.
- 现有的方法需要用户交互,影响用户体验.
研究的目的:
- 开发智能手机的持续身份验证方法.
- 在用户坐着和滚动文档时验证用户身份.
- 用传感器数据评估机器学习模型的有效性.
主要方法:
- 利用了来自H-MOG数据集的触摸事件和智能手机传感器功能.
- 整合了每个传感器的信号向量大小功能.
- 通过1类和2类实验设置评估了几种机器学习模型.
主要成果:
- 一级支持矢量机 (SVM) 模型实现了98.9%的准确性.
- 一级SVM模型实现了99.4%的F1得分.
- 信号向量大小特征被确定为高度显著.
结论:
- 使用触摸事件和传感器数据的持续身份验证非常有效.
- 机器学习模型,特别是1类SVM,提供强大的智能手机安全性.
- 拟议的方法提供了一个无声和高效的身份验证解决方案.
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