Hybrid Deep Autoencoder with Random Forest in Native SDN Intrusion Detection Environment-Reference-Cited by-同舟云学术

Hybrid Deep Autoencoder with Random Forest in Native SDN Intrusion Detection Environment

Published:2022-05-16 Issue: Volume: Page:
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Container-title:ICC 2022 - IEEE International Conference on Communications
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Author:

Isa Mohd Mat¹,Mhamdi Lotfi¹

Affiliation:

1. University of Leeds,School of Electronic and Electrical Engineering,West Yorkshire,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9837954/9838246/09838282.pdf?arnumber=9838282

Reference24 articles.

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2. Hybrid Deep Learning: An Efficient Reconnaissance and Surveillance Detection Mechanism in SDN

3. A Taxonomy and Survey of Intrusion Detection System Design Techniques, Network Threats and Datasets;hindy,2018

4. Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization

5. Network Intrusion Detection Based on Random Forest and Support Vector Machine

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