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A comprehensive node-based botnet detection framework for IoT network
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PRE
AI
DOI：10.1007/s10586-024-04379-6.png)
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Abstract
En 中文
The number of cyber-attacks targeting the Internet of Things (IoT) has elevated in the last decade. This is due to the inherent security vulnerabilities inside IoT endpoints, as well as the broad acceptance and usage of Industrial IoT. In this context, botnets have arisen as a significant risk to IoT-based infrastructures by exploiting security flaws in firmware, including weak or default passwords, to hack devices. In this article, research is performed on an Intrusion Detection System (IDS) that can be installed within an IoT device to increase visibility and help devices become more secure. The presented research framework termed a Blockchain-inspired Botnet Detection System (BDS) includes the node-level IDS. Moreover, the comprehensive architecture of the node-level BDS framework is discussed. Using the ISOT, IoT23, and BoTIoT datasets, the performance of the presented model is assessed for alerts, detection rates, detection delay, and peak CPU and memory usage. Based on the computational results effective outcomes were registered for the proposed technique.
Keywords:
Intrusion detection system
Internet of things
Node-level
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