Using Deep Learning Techniques for Network Intrusion Detection

Sara Al-Emadi, Aisha Al-Mohannadi, Felwa Al-Senaid

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

51 Citations (Scopus)

Abstract

In recent years, there has been a significant increase in network intrusion attacks which raises a great concern from the privacy and security aspects. Due to the advancement of the technology, cyber-security attacks are becoming very complex such that the current detection systems are not sufficient enough to address this issue. Therefore, an implementation of an intelligent and effective network intrusion detection system would be crucial to solve this problem. In this paper, we use deep learning techniques, namely, Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) to design an intelligent detection system which is able to detect different network intrusions. Additionally, we evaluate the performance of the proposed solution using different evaluation matrices and we present a comparison between the results of our proposed solution to find the best model for the network intrusion detection system.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages171-176
Number of pages6
ISBN (Electronic)9781728148212
DOIs
Publication statusPublished - Feb 2020
Externally publishedYes
Event2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020 - Doha, Qatar
Duration: 2 Feb 20205 Feb 2020

Publication series

Name2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020

Conference

Conference2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020
Country/TerritoryQatar
CityDoha
Period2/02/205/02/20

Keywords

  • CNN
  • Convolutional Neural Network
  • Deep Learning
  • Network Intrusion Detection
  • Network Security
  • Neural Network
  • RNN
  • Recurrent Neural Network

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