Intelligent Intrusion Detection System for APACHE WEB SERVER Empowered with Machine Learning Approaches

Authors

  • ubaid ullah Minhaj University Lahore
  • Zain Rajpoot Department of Computer Science, University of South Aisa, Lahore, Pakistan
  • Amna Ilyas Department of Computer Science, Institute for Art and Culture, Lahore, Pakistan
  • Nafisa Tahir Lecture, Institute for Art & Culture, Lahore
  • Aqsa Noor Department of Computer Science, Ncba&E, Lahore, Pakistan

Keywords:

Intrusion detection, Naïve Bayes, Machine Learning, Intrusion prediction.

Abstract

Nowadays, the online communication between vendors and customer are most familiar ways due to covid-19 pandemic. The to make this communication more effective and secure, the system requires more accurate and efficient   algorithms. So in this research work an intrusion detection system for Apache web servers is proposed. The proposed method uses the Naive Bayes machine learning algorithm for training. The data set for training is taken from IEEE. The cross validation accuracy of proposed system is 98.6%.

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Published

30-03-2022

How to Cite

ubaid ullah, Zain Rajpoot, Amna Ilyas, Nafisa Tahir, & Aqsa Noor. (2022). Intelligent Intrusion Detection System for APACHE WEB SERVER Empowered with Machine Learning Approaches . International Journal of Computational and Innovative Sciences, 1(1), 1–7. Retrieved from https://ijcis.com/index.php/IJCIS/article/view/13

Issue

Vol. 1 No. 1 (2022): March (2022)

Section

Articles

License

Creative Commons License

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

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