An empirical intrusion detection system based on XGBoost and bidirectional long‐short term model for 5G and other telecommunication technologies
Author:
Affiliation:
1. Department of Information Technology Sona College of Technology Salem Tamil Nadu India
2. School of Information Technology and Engineering Vellore Institute of Technology Vellore Tamil Nadu India
Publisher
Wiley
Subject
Artificial Intelligence,Computational Mathematics
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1111/coin.12497
Reference30 articles.
1. A Deep Gated Recurrent Unit based model for wireless intrusion detection system
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1. Retraction: ChinnathangamKarthikraja, JayaprakasamSenthilkumar, RajaduraiHariharan, Gandhi UshaDevi, YuvarajSuresh, VijayakumarMohanraj. An empirical intrusion detection system based on XGBoost and bidirectional long‐short term model for 5G and other telecommunication technologies. Comput Intell38: 1216–1231, 2022 (10.1111/coin.12497);Computational Intelligence;2024-06
2. Design of distributed network intrusion prevention system based on Spark and P2DR models;Cluster Computing;2024-05-11
3. 5G Resource Allocation Using Feature Selection and Greylag Goose Optimization Algorithm;Computers, Materials & Continua;2024
4. Stock Price Volatility Prediction in Financial Big Data on XGBoost and ARIMA Models;2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE);2023-11-02
5. Comparative research on network intrusion detection methods based on machine learning;Computers & Security;2022-10
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