A Horizontal Federated Learning Approach to IoT Malware Traffic Detection: An Empirical Evaluation with N-BaIoT Dataset-Reference-Cited by-同舟云学术

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A Horizontal Federated Learning Approach to IoT Malware Traffic Detection: An Empirical Evaluation with N-BaIoT Dataset

Published:2024-02-04 Issue: Volume:20.6 Page:1494-1506
ISSN:
Container-title:2024 26th International Conference on Advanced Communications Technology (ICACT)
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Author:

Do Phuc Hao¹,Le Tran Duc²,Vishnevsky Vladimir³,Berezkin Aleksandr¹,Kirichek Ruslan¹

Affiliation:

1. The Bonch-Bruevich Saint-Petersburg State University of Telecommunications,Saint-Petersburg,Russia

2. University of Science and Technology - The University of Danang,Da Nang,Viet Nam

3. V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences,Moscow,Russia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10471761/10471762/10471929.pdf?arnumber=10471929

Reference39 articles.

1. BuildSenSys: Reusing building sensing data for traffic prediction with cross-domain learning;Xiaochen;IEEE Transactions on Mobile Computing,2020

2. SoK: Security Evaluation of Home-Based IoT Deployments

3. The Heterogeneous Gateways in the Industrial Internet of Things

4. Energy Efficient Wireless Sensor Networks using Co-operative MIMO: A Technical Review

5. Security of the Internet of Things: Vulnerabilities, attacks, and countermeasures;Ismail;IEEE Communications Surveys & Tutorials,2019

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