Detecting Flooding, Impersonation and Injection Attacks on AWID Dataset using ML based Methods-Reference-Cited by-同舟云学术

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Detecting Flooding, Impersonation and Injection Attacks on AWID Dataset using ML based Methods

Published:2022-10-08 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA)
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Author:

Agarwal Mayank¹

Affiliation:

1. Indian Institute of Technology,Department of Computer Science & Engineering,Patna,India,801103

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9987721/9988754/09989147.pdf?arnumber=9989147

Reference18 articles.

1. Logistic regression;wright,1995

2. Comparison of Various DoS Algorithm

3. Naïve bayes;webb;Encyclopedia of Machine Learning,2010

4. Explaining AdaBoost

5. An efficient deep learning model for intrusion classification and prediction in 5G and IoT networks

Cited by 3 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. Enhancing Network Security For Kr00k Attack Detection Using Binary Grasshopper Optimization (BGO);2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22

2. Recursive Feature Selection and Intrusion Classification in NSL-KDD Dataset Using Multiple Machine Learning Methods;Communications in Computer and Information Science;2024

3. Feature Selection in Wireless Intrusion Detection System for Evil Twin Attack Detection;2023 3rd International Conference on Innovative Sustainable Computational Technologies (CISCT);2023-09-08

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