publication . Conference object . 2019

Classifying Security Attacks in IoT Networks Using Supervised Learning

Christiana Ioannou; Vasos Vassiliou;

Open Access

Published: 31 Oct 2019

Publisher: IEEE

Summary

Abstract

Machine learning models have long be proposed to detect the presence of unauthorized activity within computer networks. They are used as anomaly detection techniques to detect abnormal behaviors within the network. We propose to use Support Vector Machine (SVM) learning anomaly detection model to detect abnormalities within the Internet of Things. SVM creates its normal profile hyperplane based on both benign and malicious local sensor activity. An important aspect of our work is the use of actual IoT network traffic with specific network layer attacks implemented by us. This is in contrast to other works creating supervised learning models, with generic dataset...

doi: 10.1109/dcoss.2019.00118

Subjects

free text keywords: Intrusion detection system, Internet of Things, business.industry, business, Supervised learning, Network layer, Hyperplane, Support vector machine, Anomaly detection, Network topology, Machine learning, computer.software_genre, computer, Artificial intelligence, Computer science

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