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Updated: Jul 1, 2025

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Secure Enhancement for MQTT Protocol Using Distributed Machine Learning Framework.

Nouf Saeed Alotaibi1, Hassan I Sayed Ahmed2, Samah Osama M Kamel2

  • 1Department of Computer Science, College of Science and Humanities Al Dawadmi, Shaqra University, Dawadmi City 11911, Saudi Arabia.

Sensors (Basel, Switzerland)
|March 13, 2024
PubMed
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This study introduces an H2O-based machine learning framework to enhance Message Queuing Telemetry Transport (MQTT) security in IoT networks. The H2OXGBoost algorithm demonstrated superior accuracy in detecting and classifying MQTT attacks in real-time.

Area of Science:

  • Cybersecurity
  • Machine Learning
  • Internet of Things (IoT)

Background:

  • Message Queuing Telemetry Transport (MQTT) is widely used for device data transfer but lacks inherent security, making it vulnerable to various attacks like DDoS and MitM.
  • Existing security solutions struggle with the scalability and complexity of modern IoT environments.

Purpose of the Study:

  • To propose and evaluate a novel H2O-based distributed machine learning framework for real-time detection and classification of MQTT security threats.
  • To identify the most effective H2O algorithm for enhancing MQTT security in IoT networks.

Main Methods:

  • Development of a distributed machine learning framework utilizing H2O algorithms (Random Forests, GLM, GBM, XGBoost, DL).
  • Real-time monitoring and classification of anomalous behavior in MQTT communication.
Keywords:
H2O distributed machine learning algorithmsMQTT attacksMQTT protocoldistributed machine learningsecurity IoT

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  • Performance evaluation using metrics such as MSE, RMSE, MCE, and log loss.

    • Main Results:

    • The H2OXGBoost algorithm exhibited the highest accuracy among the evaluated H2O models for detecting MQTT attacks.
    • The proposed framework enables effective real-time monitoring and distributed classification of security threats.

    Conclusions:

    • The H2O-based distributed ML framework significantly improves MQTT protocol security, particularly within IoT environments.
    • This research offers a practical solution for enhancing the security of MQTT communication channels through advanced detection techniques.