Cloud Intrusion Detection System Based on SVM

Authors

  • Khattab M. Ali Alheeti Computer Networking Systems Department, College of Computer Sciences and Information Technology, University of Anbar, Anbar, Iraq.
  • Ali Azawii Abdu Lateef Human Resources Department, University of Anbar, Anbar, Iraq.
  • Abdulkareem Alzahrani Computer Engineering and Science Department, Faculty of Computer Science and Information Technology, Al Baha University, Al Baha, Saudi Arabia.
  • Azhar Imran Department of Creative Technologies, PAF Complex, E-9, Air University, Islamabad, Pakistan.
  • Duaa Al_Dosary Computer Networking Systems Department, College of Computer Sciences and Information Technology, University of Anbar, Anbar, Iraq.

DOI:

https://doi.org/10.3991/ijim.v17i11.39063

Keywords:

Detection system, Machine Learning; network intrusion detection; Cloud computing, SVM, Normal and abnormal behaviors.

Abstract


The demand for better intrusion detection and prevention solutions has elevated due to the current global uptick in hacking and computer network attacks. The Intrusion Detection System (IDS) is essential for spotting network attacks and anomalies, which have increased in size and scope. A detection system has become an effective security method that monitors and investigates security in cloud computing. However, several existing methods have faced issues such as low classification accuracy, high false positive rates, and low true positive rates. To solve these problems, a detection system based on Support Vector Machine (SVM) is proposed in this paper. In this method, the SVM classifier is utilized for network data classification into normal and abnormal behaviors. The Cloud Intrusion Detection Dataset is used to test the effectiveness of the suggested system. The experimental results show which the suggested system can detect abnormal behaviors with high accuracy.

Cover iJIM Vol. 17 No. 11 (2023)

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Published

2023-06-07

How to Cite

Khattab M. Ali Alheeti, Ali Azawii Abdu Lateef, Abdulkareem Alzahrani, Azhar Imran, & Duaa Al_Dosary. (2023). Cloud Intrusion Detection System Based on SVM. International Journal of Interactive Mobile Technologies (iJIM), 17(11), pp. 101–114. https://doi.org/10.3991/ijim.v17i11.39063

Issue

Vol. 17 No. 11 (2023)

Section

Papers

License

Copyright (c) 2023 Haider TH.Salim ALRikabi, Khattab M. Ali Alheeti, Ali Azawii Abdu Lateef, Abdulkareem Alzahrani, Azhar Imran, Duaa Al_Dosary

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