DT-ARO: Decision Tree-Based Artificial Rabbits Optimization to Mitigate IoT Botnet Exploitation

Author:

Almseidin Mohammad,Al-Sawwa Jamil,Alkasassbeh Mouhammd,Alzubi Maen,Alrfou Khaled

Publisher

Springer Science and Business Media LLC

Subject

Strategy and Management,Computer Networks and Communications,Hardware and Architecture,Information Systems

Reference44 articles.

1. Juniper Research: IOT CONNECTIONS TO REACH 83 BILLION BY 2024, DRIVEN BY MATURING INDUSTRIAL USE CASES. https://www.juniperresearch.com/press/iot-connections-to-reach-83-bn-by-2024 (2020). Accessed 29 Oct 2022

2. Almseidin, M., Al-Sawwa, J., Alkasassbeh, M.: Anomaly-based intrusion detection system using fuzzy logic. In: 2021 International Conference on Information Technology (ICIT), pp. 290–295. IEEE (2021)

3. Al-Kasassbeh, M., Almseidin, M., Alrfou, K., Kovacs, S.: Detection of iot-botnet attacks using fuzzy rule interpolation. J. Intell. Fuzzy Syst. 39(1), 421–431 (2020)

4. ICS Kaspersky: Threat landscape for industrial automation systems (2021)

5. Alkasassbeh, M., Almseidin, M.: Machine learning methods for network intrusion detection. arXiv preprint arXiv:1809.02610 (2018)

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