IoT Traffic Classification Techniques for Attack Detection using Machine Learning Algorithms

Authors

  • Wesam Raad

Abstract

The raise popularity of specialized Internet devices, called Internet of things (IoT), commitments conveniences and privacy concern. The largest use of IoT these days is security. The IoT attacked have been raised recently, the attacked increased by 600% since 2016. There are many ways to detect the IoT attacks. Network traffic classification is the most techniques are used in last years. The network traffic classification has many techniques. The popular technique used in last few years is Machine Learning techniques, which have been used via many Authors and get high accuracy. In this study, we explain IoT networks traffics classifications technique and IoT dataset, after that features extraction tool will be used to extract the features from dataset traffics, after that will use four machine learning algorithms which is SVM, Naive Bays, C4.5 and K-nearest. The experiment analysis show that C4.5 classifier got a good accuracy results comparing to other classifiers.

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Published

2020-05-18

Issue

Section

Articles