Research Output

Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks Against Two Objective Functions Using a Novel Dataset

  One of the important features of Routing Protocol for Low-Power and Lossy Networks (RPL) is Objective Function (OF). OF influences an IoT network in terms of routing strategies and network topology. On the other hand, detecting a combination of attacks against OFs is a cutting-edge technology that will become a necessity as next generation low-power wireless networks continue to be exploited as they grow rapidly. However, current literature lacks study on vulnerability analysis of OFs particularly in terms of combined attacks. Furthermore, machine learning is a promising solution for the global networks of IoT devices in terms of analysing their ever-growing generated data and predicting cyber-attacks against such devices. Therefore, in this paper, we study the vulnerability analysis of two popular OFs of RPL to detect combined attacks against them using machine-learning algorithms through different simulated scenarios. For this, we created a novel IoT dataset based on power and network metrics, which is deployed as part of an RPL IDS/IPS solution to enhance information security. Addressing the captured results, our machine learning approach is successful in detecting combined attacks against two popular OFs of RPL based on the power and network metrics in which MLP and RF algorithms are the most successful classifier deployment for single and ensemble models.

  • Type:

    Article

  • Date:

    20 February 2020

  • Publication Status:

    Published

  • DOI:

    10.1155/2020/2804291

  • Cross Ref:

    2804291

  • ISSN:

    1939-0114

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    006.3 Artificial intelligence

  • Funders:

    Edinburgh Napier Funded

Citation

Foley, J., Moradpoor, N., & Ochen, H. (2020). Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks Against Two Objective Functions Using a Novel Dataset. Security and Communication Networks, 2020, 1-17. https://doi.org/10.1155/2020/2804291

Authors

Keywords

IoT Dataset; Objective Functions; Combined IoT Attacks; Machine Learning; Network Metrics; Power Metrics

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