Application of Self-organizing Feature Map Neural Network Based on K-means Clustering in Network Intrusion Detection-Reference-Cited by-同舟云学术

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Application of Self-organizing Feature Map Neural Network Based on K-means Clustering in Network Intrusion Detection

Published:2019 Issue:1 Volume:61 Page:275-288
ISSN:1546-2226
Container-title:Computers, Materials & Continua
language:en
Short-container-title:

Author:

Ling Tan,Chong Li,Jingming Xia,Jun Cao

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanics of Materials,Modeling and Simulation,Biomaterials

Cited by 35 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A network intrusion detection system based on deep learning in the IoT;The Journal of Supercomputing;2024-07-13

2. Internet of Things data intrusion detection under GRU-LSTM algorithm;Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023);2024-05-07

3. Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm;International Journal of Distributed Sensor Networks;2024-03-25

4. Feature-Weighted Naive Bayesian Classifier for Wireless Network Intrusion Detection;Security and Communication Networks;2024-01-03

5. Optimization of Performance Models for Interlayer Meltblown Nonwovens with Random Forest;2023 2nd International Conference on Health Big Data and Intelligent Healthcare (ICHIH);2023-10-27

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