« Previous Article

Original Research
Received: 18 Sep 2022, Accepted: 25 Oct 2022,
 


A Novel Classifier for Cyber Attack Detection System in Industrial Internet of Things

Fathe Jeribi.


Cited By:1

Abstract
The usage of the Internet of Things (IoT) conception in the industrial sector along with applications is referred to as the Industrial Internet of Things (IIoT). Various applications have been subsumed in the IIoT. Nevertheless, cybercriminals mostly target these systems. Thus, here, a novel methodology of Cyber Attack Detection (CAD) system has been proposed in IIoT to overcome the aforementioned issue. UNSW-NB2015 and DS2OS are the two IIoT datasets utilized in this work. Initially, in both datasets, the missing values are replaced; subsequently, the feature extraction is performed. Next, by utilizing Poisson Distribution-based Naked Mole Rat Optimization Algorithm (PD-NMROA), the significant features are selected as of both datasets. After that, by employing MaHalanobis distance-based K-Means (MaH-KMeans) algorithm, the features extracted as of the datasets are normalized along with clustered. Eventually, to classify the data, the clustered features are inputted to the TanSwish - Restricted Boltzmann Dense Machines (TS-RBDMs). The experiential outcomes displayed that the proposed methodology obtained higher efficacy in contrast to the prevailing systems.

Key words: Poisson Distribution-based Naked Mole Rat Optimization Algorithm (PD-NMROA, MaHalanobis distance-based K-Means algorithm (MaH-KMeans), TanSwish - Restricted Boltzmann Dense Machines (TS-RBDMs), feature scaling, deep learning.


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Fathe Jeribi
on Google
on Google Scholar


How to Cite this Article
Pubmed Style

Fathe Jeribi. A Novel Classifier for Cyber Attack Detection System in Industrial Internet of Things. Journal of Engineering and Applied Sciences. 2022; 9(2): 30-53. doi:10.5455/jeas.2022110103

Web Style

Fathe Jeribi. A Novel Classifier for Cyber Attack Detection System in Industrial Internet of Things. https://jecasmu.org/?mno=114551 [Access: December 22, 2024]. doi:10.5455/jeas.2022110103

AMA (American Medical Association) Style

Fathe Jeribi. A Novel Classifier for Cyber Attack Detection System in Industrial Internet of Things. Journal of Engineering and Applied Sciences. 2022; 9(2): 30-53. doi:10.5455/jeas.2022110103


Vancouver/ICMJE Style

Fathe Jeribi. A Novel Classifier for Cyber Attack Detection System in Industrial Internet of Things. Journal of Engineering and Applied Sciences. (2022), [cited December 22, 2024]; 9(2): 30-53. doi:10.5455/jeas.2022110103


Harvard Style

Fathe Jeribi (2022) A Novel Classifier for Cyber Attack Detection System in Industrial Internet of Things. Journal of Engineering and Applied Sciences, 9 (2), 30-53. doi:10.5455/jeas.2022110103


Turabian Style

Fathe Jeribi. 2022. A Novel Classifier for Cyber Attack Detection System in Industrial Internet of Things. Journal of Engineering and Applied Sciences, 9 (2), 30-53. doi:10.5455/jeas.2022110103


Chicago Style

Fathe Jeribi. "A Novel Classifier for Cyber Attack Detection System in Industrial Internet of Things." Journal of Engineering and Applied Sciences 9 (2022), 30-53. doi:10.5455/jeas.2022110103


MLA (The Modern Language Association) Style

Fathe Jeribi. "A Novel Classifier for Cyber Attack Detection System in Industrial Internet of Things." Journal of Engineering and Applied Sciences 9.2 (2022), 30-53. Print. doi:10.5455/jeas.2022110103


APA (American Psychological Association) Style

Fathe Jeribi (2022) A Novel Classifier for Cyber Attack Detection System in Industrial Internet of Things. Journal of Engineering and Applied Sciences, 9 (2), 30-53. doi:10.5455/jeas.2022110103


Journal of Engineering and Applied Sciences Submit Article Track your Article
  • ISSN: 1658-6638 (print)
  • ISSN: 1658-7073 (electronic)