TY - JOUR
T1 - A comprehensive node-based botnet detection framework for IoT network
AU - Aldaej, Abdulaziz
AU - Ahanger, Tariq Ahamed
AU - Atiquzzaman, Mohammed
AU - Fazal Din, Imdad
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
PY - 2024/10
Y1 - 2024/10
N2 - 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.
AB - 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.
KW - Internet of things
KW - Intrusion detection system
KW - Node-level
UR - http://www.scopus.com/inward/record.url?scp=85190670440&partnerID=8YFLogxK
U2 - 10.1007/s10586-024-04379-6
DO - 10.1007/s10586-024-04379-6
M3 - Article
AN - SCOPUS:85190670440
SN - 1386-7857
VL - 27
SP - 9261
EP - 9281
JO - Cluster Computing
JF - Cluster Computing
IS - 7
ER -
