Ensemble technique of intrusion detection for IoT-edge platform.

Autor: Aldaej A; College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia. a.aldaej@psau.edu.sa., Ullah I; School of Computer Science, Faculty of Engineering, The University of Sydney, Sydney, NSW, 2006, Australia., Ahanger TA; Department of Management Information Systems, CoBA, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia. t.ahanger@psau.edu.sa., Atiquzzaman M; School of Computer Science, University of Oklahoma Norman, Norman, 73019-6151, USA.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2024 May 22; Vol. 14 (1), pp. 11703. Date of Electronic Publication: 2024 May 22.
DOI: 10.1038/s41598-024-62435-y
Abstrakt: Internet of Things (IoT) technology has revolutionized modern industrial sectors. Moreover, IoT technology has been incorporated within several vital domains of applicability. However, security is overlooked due to the limited resources of IoT devices. Intrusion detection methods are crucial for detecting attacks and responding adequately to every IoT attack. Conspicuously, the current study outlines a two-stage procedure for the determination and identification of intrusions. In the first stage, a binary classifier termed an Extra Tree (E-Tree) is used to analyze the flow of IoT data traffic within the network. In the second stage, an Ensemble Technique (ET) comprising of E-Tree, Deep Neural Network (DNN), and Random Forest (RF) examines the invasive events that have been identified. The proposed approach is validated for performance analysis. Specifically, Bot-IoT, CICIDS2018, NSL-KDD, and IoTID20 dataset were used for an in-depth performance assessment. Experimental results showed that the suggested strategy was more effective than existing machine learning methods. Specifically, the proposed technique registered enhanced statistical measures of accuracy, normalized accuracy, recall measure, and stability.
(© 2024. The Author(s).)
Databáze: MEDLINE
Externí odkaz: