Intrusion Detection Using Attention-Based CNN-LSTM Model

Ban Al-Omar, Zouheir Trabelsi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


With the rise of sophisticated cyberattacks and the advent of complex and diverse technological systems, traditional methods of intrusion detection have become insufficient. The inability to prevent intrusions poses a severe threat to the credibility of security services, which may result in the compromise of data confidentiality, integrity, and availability. To address this challenge, research has proposed the use of Artificial Intelligence (AI) and deep learning (DL) models to enhance the effectiveness of intrusion detection. In this study, we present an Intrusion Detection System (IDS) that utilizes attention-based Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) models. The attention mechanism of the model allows for the identification of significant features in network traffic data for more precise predictions. Using the benchmark dataset UNSW-NB15, we validate the robustness and effectiveness of our model, achieving a detection rate of over 95%. Our results emphasize the robustness and effectiveness of the proposed system, demonstrating the immense potential of AI and DL models in bolstering intrusion detection.

Original languageEnglish
Title of host publicationArtificial Intelligence Applications and Innovations - 19th IFIP WG 12.5 International Conference, AIAI 2023, Proceedings
EditorsIlias Maglogiannis, Lazaros Iliadis, John MacIntyre, Manuel Dominguez
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9783031341106
Publication statusPublished - 2023
Event19th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2023 - León, Spain
Duration: Jun 14 2023Jun 17 2023

Publication series

NameIFIP Advances in Information and Communication Technology
Volume675 IFIP
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X


Conference19th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2023


  • Attention Based
  • Intrusion Detection

ASJC Scopus subject areas

  • Information Systems and Management


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