Abstract
By successfully infecting certain numbers of nodes in an Internet of Things (IoT) platform, botmaster often relies on specific bots (infected nodes) to scan and gather information about the target nodes for onward propagation of the attack. Therefore, the bot’s processing capability to scan and executes the botmaster’s instructions relied on its memory capability. Hence, the bot’s memory efficiency determines the selection or the abandonment of the bot by the botmaster during the propagation of the attack. To defend against IoT botnets attack, there is need to accurately analyze the dynamic characteristics of the botnet propagation in a network. Although conventional IoT botnet propagation models considered certain characteristics of IoT wireless sensor networks (IoT-WSN) in analyzing the propagation time and the size of the botnet infection, the models do not consider the impact of memory-efficient bots on the size of the botnet infection. As such they are not applicable to defend the network against them. To complement this gap, this study proposed an IoT- Susceptible-Infectious-Abandon (IoT-SIA) model to analyze the impact of the memory-efficient bots on the size of the botnet infection. Consequently, based on the numerical simulation results, the memory-efficient bots have shown a direct impact on the size of the botnet infection and the propagation time of the attack.
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03 May 2021
A Correction to this paper has been published: https://doi.org/10.1007/s11277-021-08551-8
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Acknowledgements
The authors are very thankful to the Nigerian Tertiary Education Trust Fund (TETFund) and we acknowledge that this research received support from the Faculty of Computer Science and Information Technology, Universiti Putra Malaysia and the Fundamental Research Grant Scheme FRGS/1/2019/ICT03/UPM/02/1 awarded by Malaysian Ministry of Education.
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Ibrahim, M., Abdullah, M.T., Abdullah, A. et al. The Impact of Memory-Efficient Bots on IoT-WSN Botnet Propagation. Wireless Pers Commun 119, 2093–2105 (2021). https://doi.org/10.1007/s11277-021-08320-7
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DOI: https://doi.org/10.1007/s11277-021-08320-7