A Novel Approach for Detection of Cyber Attacks in MQTT-Based IIoT Systems Using Machine Learning Techniques DOI Creative Commons
Serkan Gönen

Journal of Advanced Research in Natural and Applied Sciences, Journal Year: 2024, Volume and Issue: 10(4), P. 899 - 912

Published: Dec. 31, 2024

The Internet of Things (IoT) and the Industrial (IIoT) have grown significantly in last decade, underlining increasing need for effective, secure, reliable data communication protocols. widely accepted Message Queuing Telemetry Transport (MQTT) protocol, with its structure that meets needs welding-oriented devices IoT IIoT applications, is a prime example. However, user-friendly simplicity also makes it susceptible to threats such as Dispersed Services Rejection (DDOS), Brete-Force, incorrectly shaped package attacks. This article introduces robust framework preventing defending against attacks MQTT-based systems based on theory merging expert system incorporates Adaboost model can detect anomalies by processing network traffic closed setting identifying impending threats. With design, was subjected various attack scenarios during testing, consistently detected interventions an average accuracy 92.7%, demonstrating potential use intervention detection systems. research findings not only contribute theoretical practical concerns about effective protection but offer hope future cybersecurity these

Language: Английский

ADIMPL: a dynamic, real-time and robustness attack detection model for industrial cyber-physical systems based on improved meta pseudo labels DOI
Bohan Zhang, Pan Zhang, Zhiwen Wang

et al.

Applied Intelligence, Journal Year: 2025, Volume and Issue: 55(6)

Published: Feb. 28, 2025

Language: Английский

Citations

0
Empirical evaluation of ensemble learning and hybrid CNN-LSTM for IoT threat detection on heterogeneous datasets DOI
Ahsan Nazir, Jingsha He, Nafei Zhu

et al.

The Journal of Supercomputing, Journal Year: 2025, Volume and Issue: 81(6)

Published: April 23, 2025

Language: Английский

Citations

0
Encoder decoder-based Virtual Physically Unclonable Function for Internet of Things device authentication using split-learning DOI Creative Commons

Raviha Khan,

Hossien B. Eldeeb, Brahim Mefgouda

et al.

Computers & Security, Journal Year: 2024, Volume and Issue: unknown, P. 104164 - 104164

Published: Oct. 1, 2024

Language: Английский

Citations

0
A Novel Approach for Detection of Cyber Attacks in MQTT-Based IIoT Systems Using Machine Learning Techniques DOI Creative Commons
Serkan Gönen

Journal of Advanced Research in Natural and Applied Sciences, Journal Year: 2024, Volume and Issue: 10(4), P. 899 - 912

Published: Dec. 31, 2024

The Internet of Things (IoT) and the Industrial (IIoT) have grown significantly in last decade, underlining increasing need for effective, secure, reliable data communication protocols. widely accepted Message Queuing Telemetry Transport (MQTT) protocol, with its structure that meets needs welding-oriented devices IoT IIoT applications, is a prime example. However, user-friendly simplicity also makes it susceptible to threats such as Dispersed Services Rejection (DDOS), Brete-Force, incorrectly shaped package attacks. This article introduces robust framework preventing defending against attacks MQTT-based systems based on theory merging expert system incorporates Adaboost model can detect anomalies by processing network traffic closed setting identifying impending threats. With design, was subjected various attack scenarios during testing, consistently detected interventions an average accuracy 92.7%, demonstrating potential use intervention detection systems. research findings not only contribute theoretical practical concerns about effective protection but offer hope future cybersecurity these

Language: Английский

Citations

0