An efficient deep learning model for intrusion classification and prediction in 5G and IoT networks-Reference-Cited by-同舟云学术

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

Published:2019-03 Issue: Volume: Page:
ISSN:
Container-title:2019 53rd Annual Conference on Information Sciences and Systems (CISS)
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Author:

Rezvy Shahadate,Luo Yuan,Petridis Miltos,Lasebae Aboubaker,Zebin Tahmina

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8686042/8692764/08693059.pdf?arnumber=8693059

Cited by 49 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. Analysis of Machine Learning Methods for Intrusion Detection Systems in Wireless Networks;Bulletin of Business and Economics (BBE);2024-06-01

2. MDR-TCN-BiGAtt model based IoT intrusion detection in fog environment;2024 IEEE 14th International Conference on Electronics Information and Emergency Communication (ICEIEC);2024-05-24

3. Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges, and Future Directions;IEEE Access;2024

4. FBMP-IDS: FL-Based Blockchain-Powered Lightweight MPC-Secured IDS for 6G Networks;IEEE Access;2024

5. Blockchain based federated learning for intrusion detection for Internet of Things;Frontiers of Computer Science;2023-12-23

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