Intrusion Detection System using Machine Learning

Authors

  • Jayesh Zala  Computer Engineering Department, A. D. Patel Institute of Technology, Karamsad, Gujarat, India
  • Aditya Panchal  Computer Engineering Department, A. D. Patel Institute of Technology, Karamsad, Gujarat, India
  • Advait Thakkar  Computer Engineering Department, A. D. Patel Institute of Technology, Karamsad, Gujarat, India
  • Bhagirath Prajapati  Computer Engineering Department, A. D. Patel Institute of Technology, Karamsad, Gujarat, India
  • Priyanka Puvar  Computer Engineering Department, A. D. Patel Institute of Technology, Karamsad, Gujarat, India

DOI:

https://doi.org//10.32628/CSEIT2062166

Keywords:

Intrusion Detection System, Host, Network, Detection Techniques, Support vector machine, Machine Learning, NIDS, HIDS.

Abstract

Intrusion Detection System (IDS) is a tool, or software application, that monitors network or system activity and detects malicious activity occurring. The protected evolution of the network must incorporate new threats and related approaches to avoid these threats. The key role of the IDS is to secure resources against the attacks. Several approaches, methods and algorithms of the intrusion detection help to detect a plethora of attacks. The main objective of this paper is to provide a complete system to detect intruding attacks using the Machine Learning technique which identifies the unknown attacks using the past information gained from the known attacks. The paper explains preprocessing techniques, model comparisons for training as well as testing, and evaluation technique.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2020-04-30

Issue

Volume 6, Issue 3, May-June-2020

Section

Research Articles

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How to Cite

[1]
Jayesh Zala, Aditya Panchal, Advait Thakkar, Bhagirath Prajapati, Priyanka Puvar, " Intrusion Detection System using Machine Learning, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 3, pp.61-71, May-June-2020. Available at doi : https://doi.org/10.32628/CSEIT2062166