DDoS Attack Detection Based on Random Forest-Reference-Cited by-同舟云学术

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DDoS Attack Detection Based on Random Forest

Published:2020-12-18 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE International Conference on Progress in Informatics and Computing (PIC)
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Author:

Chen Yini¹,Hou Jun²,Li Qianmu¹,Long Huaqiu³

Affiliation:

1. Nanjing University of Science and Technology,School of Computer Science and Engineering,Nanjing,China

2. Nanjing Vocational University of Industry Technology,Department of Social Science,Nanjing,China

3. Wuyi University,Intelligent Manufacturing Department,Jiangmen,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9350666/9350738/09350788.pdf?arnumber=9350788

Cited by 12 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. Detecting DDoS Attacks using Machine Learning in IoT Environment;2024 International Conference on Intelligent Systems and Computer Vision (ISCV);2024-05-08

2. Leveraging blockchain and machine learning to counter DDoS attacks over IoT network;Multimedia Tools and Applications;2024-03-20

3. Efficient Machine Learning Algorithms for DDoS Attack Detection;2024 6th International Conference on Computing and Informatics (ICCI);2024-03-06

4. Distributed Denial of Service Classification for Software-Defined Networking Using Grammatical Evolution;Future Internet;2023-12-13

5. An RF-based Low Rate DDoS Attack Real-time Detection System;2023 33rd International Telecommunication Networks and Applications Conference;2023-11-29

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