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An Iterative Convolutional Neural Network Based Malicious Node Detection (ICNNMND) Protocol For Internet of Things

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Abstract

At present Internet of Things is widely used in various products and parts in our daily life. In the future, its uses and requirements will increase. However, there are several issues with the IoT network, one of which is secure data transmission. Also, malicious nodes in the IoT network are very difficult to identify accurately and quickly, whereas it is very important to do so. In the current context, several solutions are being proposed as there is a need to focus on setting up secure IoT frameworks, and as well as the protocols that runs on them. This research proposes a secure protocol called iterative Convolutional Neural Network based Malicious Node Detection protocol that uses the erroneous assumption learning problematic technique. This protocol will make changes in the application layer, the network layer and the physical layer in order to achieve secure data transmission in IoT. The proposed ICNNMND protocol will be able to detect attacks and eliminate them hence providing maximum data accuracy in IoT. For this, machine learning method will be used and the changes in the characteristics of the malicious nodes will be learned and their boundaries be explored. Then its error variation will be calculated and the malicious nodes be differentiated.

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Data availability

The dataset generated and analysed during the current study is available from the corresponding author on reasonable request.

Code availability

The code generated for the current study is available from the corresponding author on reasonable request.

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Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Author notes

  1. Karabo Serome and Rajalakshmi Selvaraj these authors contributed equally to this work.

Authors and Affiliations

  1. Department of Computer Science and Information Systems, Botswana International University of Science and Technology (BIUST), Palapye, Central District, Botswana

    Moemedi Moka, Karabo Serome & Rajalakshmi Selvaraj

Authors
  1. Moemedi Moka
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  2. Karabo Serome
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  3. Rajalakshmi Selvaraj
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Contributions

All authors contributed equally to the study. All authors were involved in the conception and design of the study. Material preparation was performed by Moemedi Moka,and Prof. Rajalakshmi Selvaraj, data collection and analysis were performed by Moemedi Moka and Karabo Serome. The first draft of the manuscript was written by Moemedi Moka and Karabo Serome. The revision of the manuscript was done by Moemedi Moka, Prof. Rajalakshmi Selvaraj, and Karabo Serome. All authors commented on previous versions of the manuscript.

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Correspondence to Moemedi Moka.

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Moka, M., Serome, K. & Selvaraj, R. An Iterative Convolutional Neural Network Based Malicious Node Detection (ICNNMND) Protocol For Internet of Things. Wireless Pers Commun (2024). https://doi.org/10.1007/s11277-024-11459-8

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