Journal of ISMAC
IRO Journals
Volume 2 — Issue 4 — December 2020

Hybrid Intrusion Detection System for Internet of Things (IoT)

https://doi.org/10.36548/jismac.2020.4.002
Pages: 190-199
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S. Smys
Professor, Department of Computer Science and Engineering, RVS Technical Campus,
Abul Basar
Professor, Prince Mohammad Bin Fahd University
Haoxiang Wang
Department of Electrical and Computer Engineering
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How to Cite

Smys, S., Abul Basar, and Haoxiang Wang. 2020. “Hybrid Intrusion Detection System for Internet of Things (IoT)”. Journal of ISMAC 2 (4): 190-99. https://doi.org/10.36548/jismac.2020.4.002.
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Keywords

— Intrusion detection system (IDS)
— Internet of Things (IoT)
— Network attacks
Published: 30-09-2020

Abstract

Internet of things (IoT) is a promising solution to connect and access every device through internet. Every day the device count increases with large diversity in shape, size, usage and complexity. Since IoT drive the world and changes people lives with its wide range of services and applications. However, IoT provides numerous services through applications, it faces severe security issues and vulnerable to attacks such as sinkhole attack, eaves dropping, denial of service attacks, etc., Intrusion detection system is used to detect such attacks when the network security is breached. This research work proposed an intrusion detection system for IoT network and detect different types of attacks based on hybrid convolutional neural network model. Proposed model is suitable for wide range of IoT applications. Proposed research work is validated and compared with conventional machine learning and deep learning model. Experimental result demonstrate that proposed hybrid model is more sensitive to attacks in the IoT network.

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