Machine Learning Model for classification of IoT Network Traffic

Shilpa P. Khedkar, R. Aroulcanessane
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引用次数: 8

Abstract

In today's world, it becomes very important to improve network security as well as the quality of service (QoS). Internets of Things (IoT) with machine learning techniques are used to provide services to users with a classification of the network traffic. So it is very important to separate malicious traffic from normal traffic. After detecting malicious traffic it has to be blocked and forwarded the normal traffic to the specified nodes for serving the users requirements. Here, presents machine learning algorithms for classifying the network traffic, for controlling the congestion in the network.
物联网网络流量分类的机器学习模型
在当今世界,提高网络安全性和服务质量(QoS)变得非常重要。利用机器学习技术的物联网(IoT)为用户提供网络流量分类服务。因此,将恶意流量与正常流量分离是非常重要的。检测到恶意流量后,需要对其进行阻断,并将正常流量转发到指定节点,以满足用户的需求。本文提出了一种机器学习算法,用于对网络流量进行分类,以控制网络中的拥塞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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