基于实时物联网网络流量的有效负载状态预测,使用层次聚类与代优化进行代优化
Hao Zhang1, Jing Wang2, Xuanyuan Wang1
1State Grid Jibei Electric Power Company Limited, Tangshan 063000, China.
Sensors (Basel, Switzerland)
|January 11, 2025
概括
IoTGuard通过准确预测有效负载状态以检测尸网络和病毒来增强物联网 (IoT) 网络安全性. 这种方法改善了预警系统,提供了更高效和有效的防御网络威胁.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 网络工程 网络工程
背景情况:
- 物联网 (IoT) 网络越来越容易受到复杂的网络威胁,如尸网络和病毒.
- 现有的网络安全解决方案因物联网环境中的通信不稳定性和数据包丢失而难以准确地预测状态.
- 有效的有效负载状态预测对于早期检测,警告和对物联网网络攻击的快速响应至关重要.
研究的目的:
- 提出IoTGuard,一种新的网络有效负载预测器,旨在实时预测物联网网络中有效负载状态.
- 通过开发更准确,更有效的方法来解决现有的状态预测方案的局限性.
- 加强物联网网络的安全态度,以应对不断变化的网络威胁.
主要方法:
- 从物联网网络流量中实时提取应用层有效负载,使用网络有效负载分离模块.
- 通过专门的有效载荷提取模块在网络流中对有效载荷状态的分类.
- 训练有效载荷状态预测器使用标记的物联网网络有效载荷数据集.
主要成果:
- IoTGuard在预测物联网网络中的有效载荷状态方面表现出高准确性.
- 在网络有效负载预测中实现了86%的准确率,比最先进的NetZob方法高出8%.
- 与现有方法相比,训练时间大幅减少52.8%,确保执行效率.
结论:
- IoTGuard提供了一个更准确,更有效的解决方案,用于预测物联网网络中的有效负载状态.
- 拟议的方法为检测网络攻击和尸网络提供了改进的早期预警功能.
- 物联网保护 (IoTGuard) 在保护物联网环境免受普遍的网络威胁方面取得了重大进展.
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