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在物联网-WSN中连接攻击通过基于前向和后向消除的循环分析来检测

Tamil Selvi S¹, Visalakshi P¹

¹Networking and Communications, SRM Institute of Science and Technology, Kattankulathur, Tamilnadu, India.

PeerJ. Computer science

|July 10, 2024

概括

本研究介绍了一种循环分析方法 (CAM),用于检测物联网-无线传感器网络 (IoT-WSN) 中的新型CONNECT攻击. 在识别恶意节点方面,CAM可达到约99%的准确性,提高网络安全性和效率.

科学领域:

计算机科学计算机科学
网络安全网络安全
网络安全网络安全

背景情况:

物联网-无线传感器网络 (IoT-WSN) 对许多应用程序至关重要,但易受复杂的攻击.
CONNECT攻击是一种新型威胁,它破坏了IoT-WSN中的数据包传输,节点连接和CPU性能.
现有的安全措施很难有效地检测和防止这种有针对性的攻击.

研究的目的:

引入和评估基于循环分析方法 (CAM) 的新型入侵检测算法,用于检测物联网-WSN中的CONNECT攻击.
通过减轻CONNECT攻击的影响,提高物联网-WSN的效率和可靠性.
识别恶意路径和节点,同时通过多个无循环路线确保无数据传输.

主要方法:

开发了一种循环分析方法 (CAM),包括前选择和后退消除技术.
分析路由信息和网络行为,以识别恶意路径和节点.
模拟了使用Matlab软件进行性能评估的拟议CAM算法.

主要成果:

该CAM算法在检测恶意节点方面表现出卓越的准确性,达到大约99%的攻击检测准确性.
在识别和缓解 CONNECT 攻击方面表现优于传统算法.
基于恶意节点检测准确性,连接性,数据包丢失和网络流量来评估性能.

结论:

拟议的CAM算法在检测物联网-WSN中的CONNECT攻击方面非常有效,准确度非常高.
通过识别和中和威胁,CAM显著提高了网络安全和运营效率.
该方法为保护WSN免受新型和破坏性攻击提供了强大的解决方案.

关键词:

倒退淘汰方法是一种倒退淘汰方法.连接攻击连接攻击循环分析方法 (CAM)前向选择方法是前向选择的方法.无线传感器网络 (WSN) 是指无线传感器网络.

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