Protocol-Based Deep Intrusion Detection for DoS and DDoS Attacks Using UNSW-NB15 and Bot-IoT Data-Sets-Reference-Cited by-同舟云学术

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Protocol-Based Deep Intrusion Detection for DoS and DDoS Attacks Using UNSW-NB15 and Bot-IoT Data-Sets

Published:2022 Issue: Volume:10 Page:2269-2283
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zeeshan Muhammad^ORCID,Riaz Qaiser^ORCID,Bilal Muhammad Ahmad^ORCID,Shahzad Muhammad K.,Jabeen Hajira,Haider Syed Ali^ORCID,Rahim Azizur

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09656911.pdf?arnumber=9656911

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2. A comprehensive survey on deep learning‐based intrusion detection systems in Internet of Things (IoT);Expert Systems;2024-09-14

3. Self-Adaptive Lightweight Attention Module-Based BiLSTM Model for Effective Intrusion Detection;Arabian Journal for Science and Engineering;2024-08-21

4. Stacked autoencoder with weighted loss function for intrusion detection in IoT application;Multimedia Tools and Applications;2024-08-13

5. Towards Attention Mechanism in Detecting Botnet Attacks for loT Devices;2024 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD);2024-08-01

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