Journal of Cybersecurity and Information Management

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https://doi.org/10.54216/JCIM

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Volume 11 , Issue 2 , PP: 47-56, 2023 | Cite this article as | XML | Html | PDF | Full Length Article

An Encrypted Rules and Extreme Learning Machine Approach for Enhancement of Data Security

Amit Kumar Chandanan 1 *

  • 1 Department of Computer Science and Information Technology, Guru Ghasidas Vishwavidyalaya, Bilaspur, India - (chandanan.amit@ggu.ac.in)
  • Doi: https://doi.org/10.54216/JCIM.110205

    Received: November 20, 2022 Revised: January 25, 2023 Accepted: March 21, 2023
    Abstract

    Among the many uses for WSN, which is an ad hoc wireless system, are conveyance, calamity administration, industrialized observing, health observing, and so on. Intrusion Detection System (IDS) is a top-tier network security measure. In order to prevent cross-layer attacks, IDS detection rates must be high. Using a technique known as the "Rule of Thumb" or ELM (Extreme Learning Machine) algorithm, WSN is able to predict the future with a great grade of accurateness. The projected RELM provides a comprehensive overview of both the attacks and the rules for detecting them. The rules can identify threats at the different layers. If the rule-founded IDS were deployed at the sensor nodes, less data would need to be transmitted over the network, saving power. Relative to the SVM (Support Vector Machine) and BPN (Back Propagation Neural Network) on the NSL-KDD dataset, RELM evaluates ELM's detection rate. Because of its superior detection rate, ELM has been used as the foundation of the IDS deployed at the BS to protect it against intrusion. If the criteria were combined with the ELM algorithm, the resulting system would have a higher detection rate than any currently available alternative.

    Keywords :

    Secure WSN , Extreme Learning Machine , Intrusion Detection System , RELM , Support Vector Machine.

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    Cite This Article As :
    Kumar, Amit. An Encrypted Rules and Extreme Learning Machine Approach for Enhancement of Data Security. Journal of Cybersecurity and Information Management, vol. , no. , 2023, pp. 47-56. DOI: https://doi.org/10.54216/JCIM.110205
    Kumar, A. (2023). An Encrypted Rules and Extreme Learning Machine Approach for Enhancement of Data Security. Journal of Cybersecurity and Information Management, (), 47-56. DOI: https://doi.org/10.54216/JCIM.110205
    Kumar, Amit. An Encrypted Rules and Extreme Learning Machine Approach for Enhancement of Data Security. Journal of Cybersecurity and Information Management , no. (2023): 47-56. DOI: https://doi.org/10.54216/JCIM.110205
    Kumar, A. (2023) . An Encrypted Rules and Extreme Learning Machine Approach for Enhancement of Data Security. Journal of Cybersecurity and Information Management , () , 47-56 . DOI: https://doi.org/10.54216/JCIM.110205
    Kumar A. [2023]. An Encrypted Rules and Extreme Learning Machine Approach for Enhancement of Data Security. Journal of Cybersecurity and Information Management. (): 47-56. DOI: https://doi.org/10.54216/JCIM.110205
    Kumar, A. "An Encrypted Rules and Extreme Learning Machine Approach for Enhancement of Data Security," Journal of Cybersecurity and Information Management, vol. , no. , pp. 47-56, 2023. DOI: https://doi.org/10.54216/JCIM.110205