面向物联网应用的无线移动自组网网络安全研究综述:网络攻击与检测机制

IF 0.8 Q4 ROBOTICS
Satyanarayana Pamarthi, R. Narmadha
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引用次数: 15

摘要

目的当前,研究人员对MANET及其在各种环境下的性能在实践和理论领域越来越感兴趣。无线传感器网络已经开始通过互联网连接设备的感知能力和传感器节点的互联网接入能力与物联网相结合。通过保持路由器的安全来保护网络免受互联网攻击是至关重要的。设计/方法论/方法本文计划对无线传感器网络(WSN)和移动自组织网络(MANET)中的各种入侵检测和预防系统进行有效的文献综述,这些系统非常适合物联网(IoT)应用中的安全。文献综述侧重于每种贡献中集中的各种类型的攻击,并观察到预防和缓解模型的采用。此外,还分析了所使用的数据集类型、集中的攻击类型、用于实现的工具类型以及在每个贡献中分析的性能度量。最后,试图在总结这篇综述时提出几个未来的研究方向,即为MANET设计和实现IDS,以保护IoT.Findings的安全方面。它观察到了不同的攻击类型,重点关注每一种贡献以及预防和缓解模型的采用。此外,还对所使用的数据集类型、重点攻击类型、用于实现的工具类型和性能度量进行了调查。原创性/价值本文对攻击检测和预防的不同贡献、不同机器学习和深度学习模型的立场进行了文献综述,并分析了所使用的数据集类型、集中的攻击、用于实施的工具以及物联网应用网络安全的性能措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Literature review on network security in Wireless Mobile Ad-hoc Network for IoT applications: network attacks and detection mechanisms
PurposeNowadays, more interest is found among the researchers in MANETs in practical and theoretical areas and their performance under various environments. WSNs have begun to combine with the IoT via the sensing capability of Internet-connected devices and the Internet access ability of sensor nodes. It is essential to shelter the network from attacks over the Internet by keeping the secure router.Design/methodology/approachThis paper plans to frame an effective literature review on diverse intrusion detection and prevention systems in Wireless Sensor Networks (WSNs) and Mobile Ad hoc NETworks (MANETs) highly suitable for security in Internet of Things (IoT) applications. The literature review is focused on various types of attacks concentrated in each contribution and the adoption of prevention and mitigation models are observed. In addition, the types of the dataset used, types of attacks concentrated, types of tools used for implementation, and performance measures analyzed in each contribution are analyzed. Finally, an attempt is made to conclude the review with several future research directions in designing and implementing IDS for MANETs that preserve the security aspects of IoT.FindingsIt observed the different attack types focused on every contribution and the adoption of prevention and mitigation models. Additionally, the used dataset types, the focused attack types, the tool types used for implementation, and the performance measures were investigated in every contribution.Originality/valueThis paper presents a literature review on diverse contributions of attack detection and prevention, and the stand of different machine learning and deep learning models along with the analysis of types of the dataset used, attacks concentrated, tools used for implementation and performance measures on the network security for IoT applications.
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来源期刊
CiteScore
3.50
自引率
0.00%
发文量
21
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