(H-DIR) 2:一个可扩展的基于的框架,用于云物联网数据中心的异常检测和网络安全
1Department of Theoretical and Applied Sciences, Università degli Studi dell'Insubria, 21100 Varese, Italy.
Sensors (Basel, Switzerland)
|August 14, 2025
概括
本研究介绍了一个混合框架, (H-DIR) 2 (混合检测和响应),用于先进的云物联网网络安全. 它有效地检测和减轻高精度和低延迟的网络异常.
科学领域:
- 网络安全 网络安全
- 网络异常检测检测网络异常检测
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
背景情况:
- 基于云的物联网基础设施面临不断发展的网络威胁,挑战传统安全.
- 现有的系统在检测复杂的攻击时,难以扩展性,适应性和解释性.
研究的目的:
- 提出 (H-DIR) 2一种混合框架,用于检测和缓解大规模异质云物联网网络中的异常.
- 通过结合分析,神经网络和语义推理来增强网络安全.
主要方法:
- 实施了一个基于的混合框架 (H-DIR) 2,集成了香农,关联随机神经网络 (ARNNs) 和RDF/SPARQL语义推理.
- 使用一个分布式的Apache Spark 3.5.0管道进行处理和分析.
- 验证了针对SYN Flood,DAO-DIO和NTP放大攻击的真实世界数据集的框架.
主要成果:
- 在SYN洪水中实现了247毫秒的平均检测延迟和0.978的AUC.
- 改善了DAO-DIO操纵的数据包传递比率,从81.2%提高到96.4% (p < 0.01).
- 在NTP放大攻击期间,峰值负载减少了88%,显示出显著的缓解能力.
结论:
- (H-DIR) 2框架为云物联网网络安全提供了一个透明,可扩展和可重复的解决方案.
- 它为检测各种威胁建立了强大的基线,包括边缘意识和零日攻击.
- 该系统证明了对大规模数据集和终端网络的有效垂直和水平可扩展性.
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