E-ISSN 1658-7073 | ISSN 1658-6638
 

Original Research 


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

Fathe Jeribi.

SUPPLEMENTARY FILES :

  • 208-1663178051-adt-1.pdf ()
  • 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. JEAS. 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: May 24, 2023]. 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. JEAS. 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. JEAS. (2022), [cited May 24, 2023]; 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. JEAS, 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