Machine Learning based IoT-BotNet Attack Detection Using Real-time Heterogeneous Data-Reference-Cited by-同舟云学术

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Machine Learning based IoT-BotNet Attack Detection Using Real-time Heterogeneous Data

Published:2022-07-20 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)
language:
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Author:

Ahmed Aqeel¹,Tjortjis Christos²

Affiliation:

1. International Hellenic University,Data Mining and Analytics Research Group School of Science & Technology,Thessaloniki,Greece,570 01

2. Data Mining and Analytics Research Group, School of Science & Technology, International Hellenic University, Thessaloniki,570 01, Greece

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9872524/9872533/09872817.pdf?arnumber=9872817

Reference31 articles.

1. Feature Selection and Ensemble-Based Intrusion Detection System: An Efficient and Comprehensive Approach

2. IoT Malicious Traffic Classification Using Machine Learning;austin,2021

3. Detecting Cybersecurity Attacks in Internet of Things Using Artificial Intelligence Methods: A Systematic Literature Review

4. Machine learning approaches to IoT security: A systematic literature review

5. Machine Learning-Based Botnet Detection in Software-Defined Network: A Systematic Review

Cited by 1 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. A Modified Transformer Neural Network (MTNN) for Robust Intrusion Detection in IoT Networks;2023 International Telecommunications Conference (ITC-Egypt);2023-07-18

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