Network Intrusion Detection Using Deep Learning

Authors

  • Blessy S  B.E Scholar, Department of Computer Science and Engineering, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
  • Samyuktha Ravi  B.E Scholar, Department of Computer Science and Engineering, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
  • Shurabthini S  B.E Scholar, Department of Computer Science and Engineering, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
  • Amudha P  Professor,Department of Computer Science and Engineering, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India

Keywords:

Intrusion Detection, Deep Learning, Convolution Neural Network

Abstract

Intrusion-detection system aims at detecting attacks against computer systems and networks or, in general, against information systems. Though various part of encryption techniques and firewalls are used to block common attacks, attackers always finds a way in intruding the network. This creates a huge need of dynamic network intrusion detection system where it can protect from nearly all types of attacks. Since dynamic nature of the system is concerned, it should be able to provide with a self-learning mechanism. Deep learning is one of the mostly preferred algorithms in dynamic learning. This paper proposes Convolution Neural Network (CNN) algorithm for intrusion detection.

References

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Published

2021-06-30

Issue

Section

Research Articles

How to Cite

[1]
Blessy S, Samyuktha Ravi, Shurabthini S, Amudha P, " Network Intrusion Detection Using Deep Learning, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 8, Issue 3, pp.469-472, May-June-2021.