Version 1
: Received: 6 December 2019 / Approved: 7 December 2019 / Online: 7 December 2019 (17:03:34 CET)
How to cite:
Ibrahim, M.; Abdullah, M.T.; Abdullah, A.; Perumal, T. Modelling and Mitigation Strategy of IoT Botnet Propagation. Preprints2019, 2019120097. https://doi.org/10.20944/preprints201912.0097.v1
Ibrahim, M.; Abdullah, M.T.; Abdullah, A.; Perumal, T. Modelling and Mitigation Strategy of IoT Botnet Propagation. Preprints 2019, 2019120097. https://doi.org/10.20944/preprints201912.0097.v1
Ibrahim, M.; Abdullah, M.T.; Abdullah, A.; Perumal, T. Modelling and Mitigation Strategy of IoT Botnet Propagation. Preprints2019, 2019120097. https://doi.org/10.20944/preprints201912.0097.v1
APA Style
Ibrahim, M., Abdullah, M.T., Abdullah, A., & Perumal, T. (2019). Modelling and Mitigation Strategy of IoT Botnet Propagation. Preprints. https://doi.org/10.20944/preprints201912.0097.v1
Chicago/Turabian Style
Ibrahim, M., Azizol Abdullah and Thinagaran Perumal. 2019 "Modelling and Mitigation Strategy of IoT Botnet Propagation" Preprints. https://doi.org/10.20944/preprints201912.0097.v1
Abstract
Nodes in wireless sensor networks (WSN) are characterized particularly by their limited power and memory capabilities. Limited memory is an important parameter as it defines the size of the operating system and the processing code. As established previously, energy and memory efficiency is the most important evaluation factors of WSNs as they are directly related to data loss and network lifetime. However, based on our simulation results, memory efficiency determines the selection or abandon of nodes by the botmaster for the propagation of bots in an IoT infrastructure. Consequently, the node’s memory efficiency determined the spread of bots in the network and provides defense actors with an insight of the botmaster behavior for mitigation of the attack. Conventional botnet propagation and mitigation models did not consider the impact of node’s memory efficiency in the IoT platform. To address this gap, we build IoT-SIEF, a novel propagation model with forensic capability that will analyze command and control propagation behavior based on the perspective of the node’s memory efficiency. IoT-SIEF model used to explore the dynamics of propagation using numerical simulation with more than 50% outperform other models in mitigating the number of secondary bots. Consequently, it can serve as a basis for assisting the planning, design, and defense of such networks from the investigator's point of view.
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
