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Analysis of Machine Learning Algorithms with Feature Selection for Intrusion Detection Using UNSW-NB15 Dataset

  • Published:2021 Issue: Volume: Page:
  • ISSN:1556-5068
  • Container-title:SSRN Electronic Journal
  • language:en
  • Short-container-title:SSRN Journal

Author:

Kocher Geeta,Kumar Gulshan

Publisher

Elsevier BV

Reference22 articles.

1. Performance Evaluation of Intrusion Detection Systems using ANN;K A A Omer;Egyptian Computer Science Journal,2015

2. Distributed attack detection scheme using deep learning approach for Internet of Things;A A Diro;Future Generation Computer Systems,2018

3. A survey on intrusion detection systems and classification techniques;J A Khan;Int. J. Sci. Res. Sci., Eng. Technol,2016

4. Evaluation of machine learning classifiers for mobile malware detection;F A Narudin;Soft Computing,2016

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Building an intrusion detection system on UNSW‐NB15: Reducing the margin of error to deal with data overlap and imbalance;Concurrency and Computation: Practice and Experience;2024-08-22

2. An Ensemble Feature Selection Approach for Intrusion Detection Systems;Lecture Notes in Networks and Systems;2024

3. Improvement Networks Intrusion Detection System Using Artificial Neural Networks (ANN);Lecture Notes in Networks and Systems;2024

4. Anomaly Detection for IOT Systems Using Active Learning;Applied Sciences;2023-11-04

5. The Empirical Analysis of Machine Learning-Based Techniques for Improving Cyber Security;2023 6th International Conference on Contemporary Computing and Informatics (IC3I);2023-09-14
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