Towards Detection of Zero-Day Botnet Attack in IoT Networks Using Federated Learning-Reference-Cited by-同舟云学术

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Towards Detection of Zero-Day Botnet Attack in IoT Networks Using Federated Learning

Published:2023-05-28 Issue: Volume: Page:
ISSN:
Container-title:ICC 2023 - IEEE International Conference on Communications
language:
Short-container-title:

Author:

Zhang Jielun¹,Liang Shicong¹,Ye Feng¹,Hu Rose Qingyang²,Qian Yi³

Affiliation:

1. University of Dayton,Department of Electrical and Computer Engineering,Dayton,OH,USA

2. Utah State University,Department of Electrical and Computer Engineering,Logan,UT,USA

3. University of Nebraska-Lincoln,Department of Electrical and Computer Engineering,Omaha,NE,USA

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10278505/10278554/10279423.pdf?arnumber=10279423

Reference14 articles.

1. A comprehensive guide to bayesian convolutional neural network with variational inference;shridhar;ArXiv Preprint,2019

2. Correlated Parameters to Accurately Measure Uncertainty in Deep Neural Networks

3. Achieving High Availability in Inter-DC WAN Traffic Engineering

4. Communication-efficient learning of deep networks from decentralized data;mcmahan;Artificial Intelligence and Statistics,2017

5. Federated learning for malware detection in IoT devices

Cited by 5 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 novel approach of botnet detection using hybrid deep learning for enhancing security in IoT networks;Alexandria Engineering Journal;2024-09

2. Resource-Constraint Deep Forest-Based Intrusion Detection Method in Internet of Things for Consumer Electronic;IEEE Transactions on Consumer Electronics;2024-05

3. Network traffic classification based on federated semi-supervised learning;Journal of Systems Architecture;2024-04

4. Explainable Artificial Intelligence Enabled Intrusion Detection in the Internet of Things;Lecture Notes in Networks and Systems;2024

5. Cyber Attack Detection in IoT Using Enhanced Stream Classification Algorithm;Lecture Notes in Networks and Systems;2024

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