A Ddos Attack Categorization and Prediction Method Based on Machine Learning

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S.Siva saravanababu
Associate Professor, Department of Electronics and Communication Engineering

G.Saravanakumar
Professor, Department of Electronics and Communication Engineering (Karpagam College of Engineering)

Naveen V M
Final Year UG Students, Department of Electronics and Communication Engineering, (Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai, India)

Ajitesh kumar A S B
Final Year UG Students, Department of Electronics and Communication Engineering, (Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai, India)

Koushik P H
Final Year UG Students, Department of Electronics and Communication Engineering, (Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai, India)

Carolyne Sneha
Final Year UG Students, Department of Electronics and Communication Engineering, (Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai, India)

Bhuvaneswari
Final Year UG Students, Department of Electronics and Communication Engineering, (Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai, India)

Keywords

DDOSattack, KNNAlgorithm, DNNAlgorithm, Standard Scalar, Confusionmatrix, KNNclassifier technique, DNN classifier approach

Abstract

The most popular term for distributed network attacks is distributed denial of service (DDoS) attacks. These attacks employ certain limitations imposed on each arrangement asset, such as the design of the authorised organisation site. In this research, it is suggested that DDoS attack types be classified and foreseen using machine learning. The classification algorithms KNN and DNN are employed in this project's work. StandardScaler is used to pre-process the datasets. After using StandardScaler to remove the mean, the data are scaled to the unit variance. An evaluation of the model's performance was done using the confusion matrix created by the proposed project. For both Precision (PR) and Recall in the first classification, the KNN classifier technique is utilised (RE). The second classification makes use of the DNN classifier approach

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References

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20. S. Ali and Y. Li, "Learning Multilevel Auto-Encoders for DDoS Attack Detection in Smart Grid Network," in IEEE Access, vol. 7, pp. 108647-108659, 2019.

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Published
May 5, 2023
DOI https://doi.org/10.47750/jptcp.2023.30.09.030

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How to Cite
S.Siva saravanababu, G.Saravanakumar, Naveen V M, Ajitesh kumar A S B, Koushik P H, Carolyne Sneha, & Bhuvaneswari. (2023). A Ddos Attack Categorization and Prediction Method Based on Machine Learning. Journal of Population Therapeutics and Clinical Pharmacology, 30(9), 300–307. https://doi.org/10.47750/jptcp.2023.30.09.030
Issue
Vol. 30 No. 9 (2023): JPTCP
Section
Articles
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