A New Hybrid Machine Learning for Cybersecurity Threat Detection Based on Adaptive Boosting-Reference-Cited by-同舟云学术

A New Hybrid Machine Learning for Cybersecurity Threat Detection Based on Adaptive Boosting

Published:2019-03 Issue:5 Volume:33 Page:462-482
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Sornsuwit Ployphan¹,Jaiyen Saichon¹

Affiliation:

1. Advanced Artificial Intelligence Research Laboratory, Department of Computer Science, Faculty of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand

Funder

Thailand Research Fund

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2019.1582861

Reference20 articles.

1. Phishing detection based Associative Classification data mining

2. Phishing detection based Associative Classification data mining

3. A novel SVM-kNN-PSO ensemble method for intrusion detection system

4. A survey of intrusion detection systems based on ensemble and hybrid classifiers

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