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使用基于规则的支持矢量机器系统的混合方法:检测物联网中的网络威胁
M Wasim Abbas Ashraf1, Arvind R Singh2, A Pandian3
1School of Mathematics and Computer Science, Hanjiang Normal University, Shiyan, 442000, Hubei, China.
Scientific reports
|November 7, 2024
概括
本研究介绍了混合支持矢量机器基于规则的检测 (HSVMR-D) 方法,用于增强物联网 (IoT) 网络安全. HSVMR-D有效地检测出已知和新型的网络威胁,提高了资源有限的物联网环境中的安全性.
科学领域:
- 网络安全 网络安全
- 网络安全 网络安全
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
背景情况:
- 物联网 (IoT) 彻底改变了各个行业,但也带来了重大的数据安全挑战.
- 由于设备异质性,资源限制和不断变化的威胁,在物联网中检测网络威胁是困难的.
- 传统的安全措施不足以应对物联网中复杂和新型的网络威胁.
研究的目的:
- 介绍一种基于支持矢量机器基于规则的检测 (HSVMR-D) 的新型混合方法,用于全面识别物联网网络威胁.
- 通过提供可适应的威胁检测解决方案来增强物联网部署的安全姿态.
- 解决现有方法在物联网生态系统中检测多样化和不断变化的网络威胁方面的局限性.
主要方法:
- 拟议的HSVMR-D方法使用支持矢量机器 (SVM) 来根据物联网数据属性对已知和未知威胁进行分类.
- 集成了一个基于规则的检测组件,以识别已知的攻击签名和模式,提高效率.
- 这种方法使预先训练的模型适应新的物联网环境,而不需要不断的再培训,确保灵活性.
主要成果:
- 与基线研究相比,全面的实验和模拟证实了HSVMR-D方法的效率.
- 拟议的方法证明了对新型和不断变化的威胁的抵抗力增加.
- HSVMR-D实现了更少的错误阳性和更高的威胁检测准确度.
结论:
- HSVMR-D方法为识别物联网 (IoT) 中的网络威胁提供了强大的和可适应的解决方案.
- 它特别有利于以有限的资源保护物联网环境.
- 该方法通过提高威胁检测准确性和弹性来提高整体物联网安全性.
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