A Protocol-based Intrusion Detection System using Dual Autoencoders

Author:

Huang Yu-Lun1,Hung Ching-Yu2,Hu Hsiao-Te2

Affiliation:

1. National Yang Ming Chiao Tung University,Dept. of Electrical & Computer Engineering,Hsinchu,Taiwan

2. National Yang Ming Chiao Tung University,Inst. of Electrical & Control Engineering,Hsinchu,Taiwan

Publisher

IEEE

Reference15 articles.

1. Concept for Network Intrusion Detection System based on Recurrent Neural Net-work Classifier;nikolov;IEEE XXV International Scientific Conference Electronics,0

2. Intru-sion Detection systems using Real-Valued Negative Selection Algorithm with Optimized Detectors;selahshoor;2019 5th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS),0

3. Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection

4. Exploiting the Auto-Encoder Residual Error for Intrusion Detection

5. Multi-Channel Deep Feature Learning for Intrusion Detection

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1. A PSO and Random Forest-based Hybrid Model for Effective Intrusion Detection;2023 11th International Conference on Intelligent Systems and Embedded Design (ISED);2023-12-15

2. A Multi-Channel Contrastive Learning Network Based Intrusion Detection Method;Electronics;2023-02-14

3. Implementing Autoencoder Compression to Intrusion Detection System;Hybrid Intelligent Systems;2023

4. The impact of managerial attributes on cash holding and investment efficiency and the mediator role of cash holding;Journal of Islamic Accounting and Business Research;2022-10-13

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