Federated learning-based hybrid convolutional recurrent neural network for multi-class intrusion detection in IoT networks

Federated learning-based hybrid convolutional recurrent neural network for multi-class intrusion detection in IoT networks

Abstract As Internet of Things (IoT) devices leads an significant challenges in securing the systems from cyber-attacks in large-scale IoT networks. Traditional methods faces struggle to precisely detecting the complex intrusion patterns due to the heterogeneity and distributed IoT devices. There is...

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Bibliographic Details
Main Authors: Prabu Selvam, P. Karthikeyan, S. Manochitra, A. V. L. N. Sujith, T. Ganesan, Rajaram Ayyasamy, Mohammed Shuaib, Shadab Alam, A. Rajendran
Format: Article
Language:English
Published: Springer 2025-04-01
Series:Discover Internet of Things
Subjects:
Convolutional recurrent neural network
Internet of things
Man-in-the-middle
Privacy-preserving
Federated edge computing
Cyber-attacks
Online Access:https://doi.org/10.1007/s43926-025-00130-8
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https://doi.org/10.1007/s43926-025-00130-8

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