在资源有限的设备中通过生物识别和环境融合进行持续验证
Nida Zeeshan1, Makhabbat Bakyt2, Naghmeh Moradpoor1
1School of Computing, Engineering and the Built Environment, Edinburgh Napier University, Edinburgh EH10 5DT, UK.
Sensors (Basel, Switzerland)
|September 27, 2025
概括
这项研究引入了一种使用面部识别和环境传感的新型连续认证系统. 它通过适应光和声音的变化来提高安全性和效率,减少身份验证时间和能源使用.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 生物识别信息 生物识别信息
背景情况:
- 持续身份验证可以提高设备的安全性,超越单次登录.
- 现有的方法容易受到伪造,数据泄露和环境因素的影响.
- 环境条件对用户的在线安全和易受假冒和重播等攻击的影响很大.
研究的目的:
- 开发一个轻量级和安全的连续身份验证系统.
- 整合面部识别与环境传感,以实现自适应性安全.
- 提高能源效率,缩短身份验证时间.
主要方法:
- 一个卷积神经网络将面部转换为128位代码,与nonce和hashed结合.
- 一个摄像机-麦克风模块监控环境光和声音,以触发重新认证.
- 该系统使用正式的安全工具 (Scyther v1.1.3) 对各种攻击进行了验证.
主要成果:
- 该系统表现出对重播,拦截,深度假冒和假冒攻击的抵抗力.
- 平均决策时间从61.2 ± 3.4 ms减少到42.3 ± 2.1 ms.
- 每个周期的数据使用量下降了24.7%±1.8%,平均能源消耗量从21.3mJ下降到19.8mJ.
结论:
- 智能传感器触发的面部识别提供安全和节能的持续验证.
- 该系统适应环境变化,增强用户在线安全.
- 这种方法支持智能成像和基于深度学习的生物识别技术的进展.
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