A Hybrid Deep Learning Approach for Accurate Network Intrusion Detection Using Traffic Flow Analysis in IoMT Domain
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9518-9_27
Reference15 articles.
1. Binbusayyis A, Vaiyapuri T (2021) Unsupervised deep learning approach for network intrusion detection combining convolutional autoencoder and one-class SVM. Appl Intell 51:7094–7108
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3. Ilyas MU, Alharbi SA (2022) Machine learning approaches to network intrusion detection for contemporary internet traffic. Computing 104:1061–1076
4. Mamunur Rashid Md, Khan SU, Eusufzai F, Azharuddin Redwan Md, Sabuj SR, Elsharief M (2023) A federated learning-based approach for improving. Intrusion detection in industrial Internet of Things networks. Network 3(1):158–179
5. Toldinas J, Venčkauskas A, Damaševičius R, Grigaliūnas Š, Morkevičius N, Baranauskas E (2021) A novel approach for network intrusion detection using multistage deep learning image recognition. Electronics 10:1854
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