Deep Learning Approaches for Intrusion Detection
Azar Abid Salih, Kak, Shakir Fattah, Siddeeq Y. Ameen, Ageed, Zainab Salih, Subhi R. M. Zeebaree, Mohammed A. M. Sadeeq, Shakir Fattah Kak, Naaman Omar, Sadeeq, Mohammed A. M., Ibrahim Mahmood Ibrahim, Hajar Maseeh Yasin, Zryan Najat Rashid, Yasin, Hajar Maseeh, Zainab Salih Ageed, Ameen, Siddeeq Y.
Asian Journal of Research in Computer Science · pp. 50–64 · Published 17 Jun 2021
10.9734/ajrcos/2021/v9i430229Abstract
Recently, computer networks faced a big challenge, which is that various malicious attacks are growing daily. Intrusion detection is one of the leading research problems in network and computer security. This paper investigates and presents Deep Learning (DL) techniques for improving the Intrusion Detection System (IDS). Moreover, it provides a detailed comparison with evaluating performance, deep learning algorithms for detecting attacks, feature learning, and datasets used to identify the advantages of employing in enhancing network intrusion detection.
Cited by 71
Fairoz Q. Kareem, Kak, Shakir Fattah, Siddeeq Y. Ameen, Ahmed, Dindar Mikaeel, Azar Abid Salih, Dindar Mikaeel Ahmed, Shakir Fattah Kak, Hajar Maseeh Yasin, Ibrahim Mahmood Ibrahim, Yasin, Hajar Maseeh, Ahmed, Awder Mohammed, Awder Mohammed Ahmed, Ameen, Siddeeq Y., Zryan Najat Rashid, Naaman Omar, Kareem, Fairoz Q. · Asian Journal of Research in Computer Science · 2021
Marwa Mahfodh Abdulqadir, Dino, Hivi Ismat, Azar Abid Salih, Omar M. Ahmed, Ibrahim, Rowaida Khalil, Dathar Abas Hasan, Lailan M. Haji, Sharif, Karzan H., Sarkar Hasan Ahmed, Rowaida Khalil Ibrahim, Ahmed, Sarkar Hasan, Hasan, Dathar Abas, Karzan H. Sharif, Haji, Lailan M., Hivi Ismat Dino · Asian Journal of Research in Computer Science · 2021
Salim, Nareen O. M., Arshad A. Hussein, Adel AL-Zebari, Kak, Shakir Fattah, Naaman Omar, Karwan Jameel Merceedi, Abdulraheem Jamil Ahmed, Nareen O. M. Salim, Sheren Sadiq Hasan, Ahmed, Abdulraheem Jamil, Shakir Fattah Kak, Ibrahim Mahmood Ibrahim, Hasan, Sheren Sadiq, Hajar Maseeh Yasin, Yasin, Hajar Maseeh, Azar Abid Salih · Asian Journal of Research in Computer Science · 2021
Gulistan Ahmead Ismael, Salim, Nareen O. M., Azar Abid Salih, Kak, Shakir Fattah, Adel AL-Zebari, Naaman Omar, Karwan Jameel Merceedi, Ahmed, Abdulraheem Jamil, Abdulraheem Jamil Ahmed, Ismael, Gulistan Ahmead, Nareen O. M. Salim, Sheren Sadiq Hasan, Shakir Fattah Kak, Hasan, Sheren Sadiq, Ibrahim Mahmood Ibrahim, Hajar Maseeh Yasin, Yasin, Hajar Maseeh · Asian Journal of Research in Computer Science · 2021
Nijaguna Gollara Siddappa, V. Bhandage, Praveenkumar S Challagidad · Biomedical Signal Processing and Control · 2026
CH Sai Vijaya, T. Aruna, K. Yashaswini · 2026 9th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech) · 2026
R. M., Anagha Deshpande, Anjali · 2026 Contemporary Computing Innovations Conference (CCIC) · 2026
S. Rizvi, Rimo Bhuiyan, Ferdaus Anam Jibon · 2026 5th International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE) · 2026
Maira Khalid, Ahmed Raza Mohsin, Jehad Ali · Cluster Computing · 2025
Karthikeyan Kaliyaperumal, Raja Sarath Kumar Boddu, S. K. Oruganti · International Journal of Basic and Applied Sciences · 2025
Showing 49 of 71 known citations — external sources report more than can currently be individually listed.
Related research
- Automatic Segmentation of Organ at Risk in Head and Neck Cancer CT Images Using Medical Open Network for Artificial Intelligence (MONAI) with Deep Learning Techniques — shares topic coverage
- Diagnostic Accuracy of Artificial Intelligence for Breast Cancer Detection: A Systematic Review — shares topic coverage
- Leveraging Deep Learning Algorithms for Predicting Power Outages and Detecting Faults: A Review — shares topic coverage
- Bridging Prenatal Diagnostics and AI: A Systematic Review and Meta-Analysis of the Efficacy of Advanced Algorithms in Identifying Congenital Fetal Abnormalities — shares topic coverage
- Applications of Deep Learning in Predicting the Risk of Metabolic Syndrome from Lifestyle and Behavioral Factors: A Scoping Review — shares topic coverage
Article metrics
Real usage data collected on this platform.
161
Page views
0
PDF downloads
36
Outbound clicks
71
Citations
Views over time
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
Traffic sources
Referring site, by host.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.