通过通道状态信息进行优化身份验证,用于信息系统中双因素用户验证
Chuangeng Tian1, Fanjia Li1,2, Xiaomeng Liu2
1School of Information and Electrical Engineering, Xuzhou University of Technology, Xuzhou 221000, China.
Sensors (Basel, Switzerland)
|April 26, 2025
概括
本研究引入了一种使用通道状态信息 (CSI) 和按键动态的新型双因素身份验证系统. 这种增强的安全方法比现有方法提高了用户识别准确率2-3%.
科学领域:
- 计算机科学 计算机科学
- 信息安全 信息安全
- 信号处理 信号处理
背景情况:
- 传统的身份验证方法,如密码和生物识别,容易受到安全漏洞的攻击.
- 现有的系统缺乏强大的防御,防止伪造,盗窃和侵犯隐私.
- 需要先进的身份验证技术来增强系统安全性和用户隐私.
研究的目的:
- 提出一个双因素身份验证框架,将通道状态信息 (CSI) 与传统方法相结合.
- 为了利用独特的CSI变化从用户特定的键盘按键动态生物识别特征提取.
- 提高信息系统中用户身份验证的安全性和可靠性.
主要方法:
- 使用了一个信号处理管道,涉及Hampel过,Butterworth低通过和波形变换消噪.
- 功能提取包括双门移动窗口,子载体选择和主要组件分析 (PCA).
- 一个经过随机超参数搜索训练的内核支持向量机 (SVM) 分类器被用于分类.
主要成果:
- 拟议的方法根据按键动态从CSI中提取歧视性生物识别特征.
- 信号处理和特征提取技术有效地减少了噪音和维度.
- 该SVM模型在CSI特征模式的分类中实现了高精度.
结论:
- 集成的CSI和按键动态框架提供了增强的用户身份验证安全性.
- 开发的信号处理和机器学习管道显著提高了识别精度.
- 实验结果表明,与当前的算法相比,用户识别准确度有2-3%的改善.
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