音频解锁:通过声学签名和一类分类器进行设备对设备的身份验证
Alfred Anistoroaei1, Patricia Iosif1, Camelia Burlacu1
1Faculty of Automatics and Computers, Politehnica University of Timisoara, 300223 Timisoara, Romania.
Sensors (Basel, Switzerland)
|November 13, 2025
概括
本研究介绍了用于使用一类分类来验证设备的声学指纹识别. 这种方法可以从一个庞大的池中识别单个设备,提高现实应用程序的安全性.
科学领域:
- 网络安全 网络安全
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 设备对设备的认证利用了麦克风和扬声器的制造变化.
- 以前的方法专注于多类识别,不适合大型未知设备池.
- 现实世界的身份验证需要从众多未被跟踪的设备中识别一个单一的设备.
研究的目的:
- 开发一个强大的设备对设备认证系统,使用声学指纹.
- 实施单一类别分类,以识别单一合法设备.
- 探索基于云的部署,以实现高效的计算和数据存储.
主要方法:
- 使用一类分类算法:一类支持向量机和局部异常因素.
- 从制造变化中获得的声学指纹上训练模型.
- 在智能手机和汽车头部上部署和测试了该系统.
主要成果:
- 在各种设备上实现了50%至100%的识别率.
- 在不同的环境条件下评估性能:距离,高度和部件老化.
- 证明了用于身份验证任务的基于云计算的处理可行性.
结论:
- 一个类别的分类有效地使使用声学指纹从大型池中识别单个设备.
- 拟议的系统在各种环境中,包括车载系统,显示出安全身份验证的前景.
- 环境因素和组件老化带来了挑战,但在威胁模型中提出了解决方案.
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