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Feature Extraction and Artificial Intelligence-Based Intrusion Detection Model for a Secure Internet of Things Networks

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Illumination of Artificial Intelligence in Cybersecurity and Forensics

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 109))

Abstract

Security has been a concern in recent years, especially in the Internet of Things (IoT) system environment, where security and privacy are of great importance. Our lives have significantly transformed positively with the emergence of cutting-edge technologies like big data, edge and cloud computing, artificial intelligence (AI) with the help of the Internet, coupled with the generations of symmetric and asymmetric data distribution using highly valued real-time applications. Yet, these cut-edge technologies come with daily disastrous ever-increasing cyberattacks on sensitive data in the IoT-based environment. Hence, there is a continued need for groundbreaking strengths of AI-based models to develop and implement intrusion detection systems (IDSs) to arras and mitigate these ugly cyber-threats with IoT-based systems. Therefore, this chapter discusses the security issues within IoT-based environments and the application of AI models for security and privacy in IoT-based for a secure network. The chapter proposes a hybrid AI-model framework for intrusion detection in an IoT-based environment and a case study using CIC-IDS2017and UNSW-NB15 to test the proposmodel's performance. The model performed better with an accuracy of 99.45%, with a detection rate of 99.75%. The results from the proposed model show that the classifier performs far better when compared with existing work using the same datasets, thus prove more effective in the classification of intruders and attackers on IoT-based systems.

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Authors and Affiliations

  1. Department of Computer Science, University of Ilorin, Ilorin, Nigeria

    Joseph Bamidele Awotunde

  2. Department of Computer Science and Communication, Østfold University College, Halden, Norway

    Sanjay Misra

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  1. Joseph Bamidele Awotunde
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Correspondence to Joseph Bamidele Awotunde .

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Editors and Affiliations

  1. Østfold University College, Halden, Norway

    Sanjay Misra

  2. Computer Science and Engineering, Sri Sivasubramaniya Nadar College of Engineering, Chennai, Tamil Nadu, India

    Chamundeswari Arumugam

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Awotunde, J.B., Misra, S. (2022). Feature Extraction and Artificial Intelligence-Based Intrusion Detection Model for a Secure Internet of Things Networks. In: Misra, S., Arumugam, C. (eds) Illumination of Artificial Intelligence in Cybersecurity and Forensics. Lecture Notes on Data Engineering and Communications Technologies, vol 109. Springer, Cham. https://doi.org/10.1007/978-3-030-93453-8_2

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