A Review of Deep Learning Techniques for Network Intrusions Detection towards Efficient Model Developments-Reference-Cited by-同舟云学术

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A Review of Deep Learning Techniques for Network Intrusions Detection towards Efficient Model Developments

Published:2022-04-17 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Nigeria 4th International Conference on Disruptive Technologies for Sustainable Development (NIGERCON)
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Author:

Alowolodu Olufunso Dayo¹,Adetunmbi Adebayo Olusola²,Mebawondu Jacob Olorunshogo³,Mebawondu Olamatanmi Josephine²

Affiliation:

1. Federal University of Technology Akure,Department of Cyber Security,Akure,Nigeria

2. Federal University of Technology Akure,Department of Computer Science,Akure,Nigeria

3. Federal Polytechnic Nasarawa,Department of Computer Science,Nasarawa,Nigeria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9802998/9802999/09803080.pdf?arnumber=9803080

Reference57 articles.

1. Distributed Abnormal Behavior Detection Approach Based on Deep Belief Network and Ensemble SVM Using Spark

2. A Fast Learning Algorithm for Deep Belief Nets

3. Deep learning in neural networks: An overview. Neural networks;schmidhuber,2015

4. Cloud-Based Cyber-Physical Intrusion Detection for Vehicles Using Deep Learning

5. Learning long-term dependencies with gradient descent is difficult

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