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Internet of Things: A Survey on Fused Machine Learning-Based Intrusion Detection Approaches

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Advanced Machine Intelligence and Signal Processing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 858))

Abstract

The Internet of Things (IoT) connects billions of interconnected devices that can exchange information with each other with minimal user intervention. The goal of IoT is to become accessible to anyone, anytime, and anywhere. IoT has engaged in multiple fields, including education, health care, businesses, and smart home. Security and privacy issues have been significant obstacles to the widespread adoption of IoT. IoT devices cannot be entirely secure from threats; detecting attacks in real-time is essential for securing devices. In the real-time communication domain and especially in IoT, security and protection are the major issues. The resource-constrained nature of IoT devices makes traditional security techniques difficult. In this paper, the research work carried out in IoT intrusion detection system is presented. The deep learning methods are explored to provide an effective security solution for IoT intrusion detection systems. Then, the advantages and disadvantages of the methodology are discussed. Further, the open issues for future trends are provided.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Maulana Azad National Institute of Technology, Bhopal, India

    Priyanka Gupta, Lokesh Yadav & Deepak Singh Tomar

Authors
  1. Priyanka Gupta
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  2. Lokesh Yadav
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  3. Deepak Singh Tomar
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Corresponding authors

Correspondence to Lokesh Yadav or Deepak Singh Tomar .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Arunachal Pradesh (NITAP), Itanagar, Arunachal Pradesh, India

    Deepak Gupta

  2. Department of Computer Science and Engineering, National Institute of Technology Arunachal Pradesh (NITAP), Itanagar, Arunachal Pradesh, India

    Koj Sambyo

  3. School of Computer Science, Faculty of Engineering and IT, University of Technology, Sydney, NSW, Australia

    Mukesh Prasad

  4. Department of Information Technology, Indian Institute of Information Technology (IIIT), Allahabad, Uttar Pradesh, India

    Sonali Agarwal

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Gupta, P., Yadav, L., Tomar, D.S. (2022). Internet of Things: A Survey on Fused Machine Learning-Based Intrusion Detection Approaches. In: Gupta, D., Sambyo, K., Prasad, M., Agarwal, S. (eds) Advanced Machine Intelligence and Signal Processing. Lecture Notes in Electrical Engineering, vol 858. Springer, Singapore. https://doi.org/10.1007/978-981-19-0840-8_11

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