智能建筑的网络安全智能传感器框架:基于AI的入侵检测和对物联网攻击的弹性
Md Abubokor Siam1, Khadeza Yesmin Lucky1, Syed Nazmul Hasan2
1College of Business, Westcliff University, Irvine, CA 92614, USA.
Sensors (Basel, Switzerland)
|December 31, 2025
概括
本研究介绍了一种人工智能驱动的入侵检测系统 (IDS),用于保护智能建筑物免受物联网 (IoT) 网络攻击. 该框架增强了对拒绝服务和未经授权访问等威胁的抵御能力.
科学领域:
- 网络安全 网络安全
- 人工智能的人工智能
- 智能建筑技术 智能建筑技术
背景情况:
- 智能建筑物中物联网 (IoT) 设备的扩散造成了重要的网络安全漏洞.
- 针对建筑管理系统 (BMS) 和HVAC等关键基础设施的攻击可能会损害建筑安全和功能.
- 现有的安全措施可能无法充分解决基于物联网的网络威胁的不断变化的局面.
研究的目的:
- 为智能建筑物展示一种新的网络安全智能传感器框架.
- 加强对物联网相关网络攻击的检测,分类和应对.
- 改善智能建筑基础设施的整体网络安全态度.
主要方法:
- 使用机器学习算法开发自动入侵检测系统 (IDS).
- 智能传感器网络与基于人工智能的分析集成,用于持续监控.
- 实施预测建模和自动响应机制,以缓解威胁.
主要成果:
- 拟议的框架显示了各种网络攻击的高检测率.
- 观察到低误报警频率,表明系统的准确性.
- 实现了对检测到的威胁的快速响应时间,最大限度地减少了潜在的损害.
结论:
- 人工智能增强的网络安全系统对于保护基于物联网的智能建筑至关重要.
- 开发的框架为增强智能建筑物应对网络威胁的弹性提供了一个有希望的解决方案.
- 持续监控和自动响应是智能环境中有效物联网安全的关键.
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