A novel hierarchical attention-based triplet network with unsupervised domain adaptation for network intrusion detection-Reference-Cited by-同舟云学术

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A novel hierarchical attention-based triplet network with unsupervised domain adaptation for network intrusion detection

Published:2022-09-09 Issue: Volume: Page:
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Lan Jinghong^ORCID,Liu Xudong,Li Bo,Zhao Jun

Funder

2020 Industrial Internet Innovation and Development Project-the Key Project of Intelligent Connected Vehicle Safety Inspection Platform

Opening Project of Shanghai Trusted Industrial Control Platform

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-022-04076-0.pdf

Reference57 articles.

1. Yang J, Chen X, Chena S, Jiang X, Tan X (2021) Conditional variational auto-encoder and extreme value theory aided two-stage learning approach for intelligent fine-grained known/unknown intrusion detection. IEEE Transactions on Information Forensics and Security

2. Kan X, Fan Y, Fang Z, Cao L, Xiong NN, Yang D, Li X (2021) A novel iot network intrusion detection approach based on adaptive particle swarm optimization convolutional neural network. Inform Sci 568:147–162

3. Khan IA, Pi D, Khan N, Khan ZU, Hussain Y, Nawaz A, Ali F (2021) A privacy-conserving framework based intrusion detection method for detecting and recognizing malicious behaviours in cyber-physical power networks. Appl Intell 51(10):7306–7321

4. Kravchik M, Shabtai A (2021) Efficient cyber attack detection in industrial control systems using lightweight neural networks and pca. IEEE Transactions on Dependable and Secure Computing

5. Chou D, Jiang M (2021) A survey on data-driven network intrusion detection. ACM Comput Surv (CSUR) 54(9):1–36

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1. A Holistic review and performance evaluation of unsupervised learning methods for network anomaly detection;International Journal on Smart Sensing and Intelligent Systems;2024-04-01

2. An Intrusion Detection Method for Industrial Internet Fusing Multi-Scale TCN and Transformer Network;Lecture Notes in Computer Science;2024

3. An Effective Method for Detecting Unknown Types of Attacks Based on Log-Cosh Variational Autoencoder;Applied Sciences;2023-11-19

4. An Autoencoder-Based Hybrid Detection Model for Intrusion Detection With Small-Sample Problem;IEEE Transactions on Network and Service Management;2023

5. An Attention-Based Convolutional Neural Network for Intrusion Detection Model;IEEE Access;2023

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