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Machine Learning-Driven Approach for DDOS Attacks Detection using Neural-Based Networks: A Proficiency Study

Authors

  • Abdul Ghani Ansari

    Department of Information Technology, QUEST Nawabshah
    Author

  • Fareed Ahmed Jokhio

    Department of Computer Systems Engineering, QUEST Nawabshah
    Author

  • Muhammad Shehram Shah Syed

    Department of Software Engineering, Mehran University of Engineering & Technology, Jamshoro, Pakistan
    Author

  • Hina Dharejo

    Department of Information Technology, QUEST Nawabshah
    Author

  • Fayaz Ahmed Memon

    Department of Software Engineering, QUEST Nawabshah.
    Author

DOI:

https://doi.org/10.22581/muet1982.3330

Keywords:

Knowledge Discovery Dataset (KDD) , Artificial Neural Network (ANN) , Distributed Denial of Service (DDoS) Attacks , Resilient Backpropagation , Fletcher-Powell Conjugate Gradient , Scaled Conjugate Gradient

Abstract

Cyber-attacks pose significant threats to the Internet and its connected resources, causing harm to institutions and governments. Advanced technologies like cloud computing, the Internet of Things (IoT), and Artificial Intelligence (AI) have made these attacks harder to detect. Botnets, controlled by malicious actors, are at the core of many Internet attacks, including Distributed Denial of Service (DDoS) attacks. Despite years of DDoS incidents, effective defense mechanisms are lacking. In our research, we use Resilient Backpropagation, Fletcher-Powell Conjugate Gradient (FPCG), and Scaled Conjugate Gradient with three Artificial Neural Network (ANN) models: Feedforward Neural Network (FFNN), Cascade-Forward Neural Network (CFFNN), and Fitnet Neural Network (FNN) to detect DDoS attacks. The results showed that the FNN achieved higher accuracy in less time.

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Published

2025-07-01

Issue

Vol. 44 No. 3 (2025): July Issue

Section

Articles

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Copyright (c) 2025 Mehran University Research Journal of Engineering and Technology

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Machine Learning-Driven Approach for DDOS Attacks Detection using Neural-Based Networks: A Proficiency Study. (2025). Mehran University Research Journal of Engineering and Technology, 44(3), 206-218. https://doi.org/10.22581/muet1982.3330

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