Threat analysis of IoT networks using artificial neural network intrusion detection system

Hodo, Elike Komi and Bellekens, Xavier and Hamilton, Andrew and Dubouilh, Pierre-Louis and Iorkyase, Ephraim Tersoo and Tachtatzis, Christos and Atkinson, Robert (2016) Threat analysis of IoT networks using artificial neural network intrusion detection system. In: International Symposium on Networks, Computers and Communications, 2016-05-11 - 2016-05-13, Tunisia.

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Abstract

The Internet of things (IoT) network is still in its infancy and has attracted much interest in many industrial sectors including medical fields, logistics tracking, smart cities and automobiles. However as a paradigm, it is susceptible to a range of significant intrusion threats. This paper presents a threat analysis of the IoT and uses an Artificial Neural Network (ANN) to combat these threats. A multi-level perceptron, a type of supervised ANN, is trained using an IoT Data set, then is assessed on its ability to thwart Distributed Denial of Service (DDoS/DoS) attacks. This paper focuses on the classification of normal and threat patterns on an IoT Network. The ANN procedure is validated against a simulated IoT network. The experimental results demonstrate 99.4% accuracy and can successfully detect various DDoS/DoS attacks.

ORCID iDs

Hodo, Elike Komi ORCID logoORCID: https://orcid.org/0000-0002-8686-3418, Bellekens, Xavier ORCID logoORCID: https://orcid.org/0000-0003-1849-5788, Hamilton, Andrew ORCID logoORCID: https://orcid.org/0000-0002-8436-8325, Dubouilh, Pierre-Louis ORCID logoORCID: https://orcid.org/0000-0002-5858-6935, Iorkyase, Ephraim Tersoo ORCID logoORCID: https://orcid.org/0000-0002-1995-4387, Tachtatzis, Christos ORCID logoORCID: https://orcid.org/0000-0001-9150-6805 and Atkinson, Robert ORCID logoORCID: https://orcid.org/0000-0002-6206-2229;
  • Item type:Conference or Workshop Item(Paper)
    ID code:57079
    Dates:
    Date
    Event
    14 May 2016
    Published
    25 March 2016
    Accepted
    Notes:(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:25 Jul 2016 13:35
    Last modified:02 Dec 2024 21:24
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/57079
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