Abstract
Nowadays, Internet of Things (IoT) technology is widely expanding and the number of objects connected to the internet is expected to exceed 50 billion by 2020. The unprecedented amount of data generated by such a huge number of devices raises additional security and privacy threats that require bespoke countermeasure solutions. In this respect, this paper presents a new Artificial Intelligent Intrusion Detection System For Software Defined IoT Networks termed A2ISDIoT. The proposed IDS system integrates the unsupervised machine-learning technique with the Software-Defined Network (SDN) paradigm to ensure IoT security. The experimental results prove that the proposed A2ISDIoT can effectively detect intrusions and improve the network immunity against malicious nodes.
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Ben Elhadj, H., Jmal, R., Chelligue, H., Fourati, L.C. (2020). A2ISDIoT: Artificial Intelligent Intrusion Detection System for Software Defined IoT Networks. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2020. Advances in Intelligent Systems and Computing, vol 1150. Springer, Cham. https://doi.org/10.1007/978-3-030-44038-1_73
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DOI: https://doi.org/10.1007/978-3-030-44038-1_73
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