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Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks against Two Objective Functions Using a Novel Dataset
Joint Authors
Foley, John
Moradpoor, Naghmeh
Ochenyi, Henry
Source
Security and Communication Networks
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-20
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Information Technology and Computer Science
Abstract EN
One of the important features of routing protocol for low-power and lossy networks (RPLs) is objective function (OF).
OF influences an IoT network in terms of routing strategies and network topology.
On the contrary, 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 cyberattacks 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.
American Psychological Association (APA)
Foley, John& Moradpoor, Naghmeh& Ochenyi, Henry. 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،Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1208381
Modern Language Association (MLA)
Foley, John…[et al.]. Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks against Two Objective Functions Using a Novel Dataset. Security and Communication Networks No. 2020 (2020), pp.1-17.
https://search.emarefa.net/detail/BIM-1208381
American Medical Association (AMA)
Foley, John& Moradpoor, Naghmeh& Ochenyi, Henry. 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. Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1208381
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208381