journal article·2023Open access

Intrusion Detection System with Customized Machine Learning Techniques for NSL-KDD Dataset

Mohammed Zakariah, Salman A. AlQahtani, Abdulaziz M. Alawwad, Abdullilah A. Alotaibi

Computers, Materials & Continua· Volume 77· Issue 3

Abstract

Modern networks are at risk from a variety of threats as a result of the enormous growth in internet-based traffic. By consuming time and resources, intrusive traffic hampers the efficient operation of network infrastructure.... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Network Security and Intrusion Detection · Internet Traffic Analysis and Secure E-voting · Advanced Malware Detection Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (37)

Show source-provided references
1. Improving intrusion detection system using artificial neural network10.14569/IJACSA.2020.0110670 ↗
2. Deep and machine learning approaches for anomaly-based intrusion detection of imbalanced network traffic10.1109/LSENS.2018.2879990 ↗
3. On the evaluation of network intrusion detection systems: Statistical analysis of CIDDS-001 dataset using machine learning techniques
4. Statistical analysis of CIDDS-001 dataset for network intrusion detection systems using distance-based machine learning10.1016/j.procs.2017.12.091 ↗
5. An in-depth experimental study of anomaly detection using gradient boosted machine10.1007/s00521-017-3128-z ↗
6. TSE-IDS: A two-stage classifier ensemble for an intelligent anomaly-based intrusion detection system10.1109/ACCESS.2019.2928048 ↗
7. A novel hierarchical intrusion detection system based on decision tree and rules-based models
8. A survey on machine learning based intrusion detection system on NSL-KDD dataset10.5120/ijca2020920343 ↗
9. Network intrusion detection system using deep learning method with KDD Cup’99 Dataset
10. IoT-KEEPER: Detecting malicious IoT network activity using online traffic analysis at the edge10.1109/TNSM.2020.2966951 ↗
11. Intrusion detection in IoT using artificial neural networks on UNSW-15 Dataset
12. Network intrusion detection using supervised machine learning technique with feature selection
13. A deep learning approach to network intrusion detection10.1109/TETCI.2017.2772792 ↗
14. P. Peter and G. Louppe, “Gradient boosted regression trees in scikit-learn,” in PyData 2014, London, UK, 2014.
15. Scikit-learn: Machine learning in Python
16. Performance analysis of intrusion detection systems using a feature selection method on the UNSW-NB15 dataset
17. Adaptive feature mapping for customizing deep learning-based facial expression recognition model10.1109/ACCESS.2018.2805861 ↗
18. A deep learning approach for intrusion detection using recurrent neural networks10.1109/ACCESS.2017.2762418 ↗
19. Network intrusion detection system: A systematic study of machine learning and deep learning approaches10.1002/ett.4150 ↗
20. Deep learning approach for intelligent intrusion detection system10.1109/ACCESS.2019.2895334 ↗
21. TIDCS: A dynamic intrusion detection and classification system based feature selection10.1109/ACCESS.2020.2994931 ↗
22. A new intrusion detection system based on fast learning network and particle swarm optimization10.1109/ACCESS.2018.2820092 ↗
23. A supervised machine learning-based solution for efficient network intrusion detection using ensemble learning based on hyperparameter optimization10.1007/s41870-022-01115-4 ↗
24. Random neural network based novel decision-making framework for optimized and autonomous power control in LTE uplink system10.1016/j.phycom.2015.11.004 ↗
25. A. F. Agarap, “Deep learning using rectified linear units (relu),” arXiv preprint. arXiv:1803.08375, 2018.
26. Botnet attack intrusion detection in IoT enabled automated guided vehicles
27. An ensemble model for intrusion detection in the Internet of Softwarized Things
28. Federated learning for intrusion detection system: Concepts, challenges and future directions10.1016/j.comcom.2022.09.012 ↗
29. Biometric authentication-based intrusion detection using artificial intelligence Internet of Things in smart city10.3390/en15197430 ↗
30. A deep learning technique for intrusion detection system using a recurrent neural networks based framework10.1016/j.comcom.2022.12.010 ↗
31. A deep learning method with filter based feature engineering for wireless intrusion detection system10.1109/ACCESS.2019.2905633 ↗
32. A hybrid intrusion deection system based on scalable K-Means+ random forest and deep learning10.1109/ACCESS.2021.3082147 ↗
33. Deep learning methods on network intrusion detection using NSL-KDD dataset10.1109/ACCESS.2020.2972627 ↗
34. Recurrent deep learning-based feature fusion ensemble meta-classifier approach for intelligent network intrusion detection system10.1016/j.compeleceng.2022.108156 ↗
35. Wagle · Recent Advances in Artificial Intelligence and Data Engineering · 2022 · 3
36. A machine learning-based intrusion detection for detecting internet of things network attacks10.1016/j.aej.2022.02.063 ↗
37. Recurrent deep learning-based feature fusion ensemble meta-classifier approach for intelligent network intrusion detection system