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
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...
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
Related Organizations
Funded by
EC| RISE
Project
RISE
Research Center on Interactive Media, Smart System and Emerging Technologies
  • Funder: European Commission (EC)
  • Project Code: 739578
  • Funding stream: H2020 | SGA-CSA
Communities
Rural Digital Europe
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