Federated Learning-Based Intrusion Detection in IoT Networks: Performance Evaluation and Data Scaling Study

This paper presents a large-scale empirical study aimed at identifying the optimal local deep learning model and data volume for deploying intrusion detection systems (IDS) on resource-constrained IoT devices using federated learning (FL). While previous studies on FL-based IDS for IoT have primaril...

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Autors principals:	Nurtay Albanbay, Yerlan Tursynbek, Kalman Graffi, Raissa Uskenbayeva, Zhuldyz Kalpeyeva, Zhastalap Abilkaiyr, Yerlan Ayapov
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2025-07-01
Col·lecció:	Journal of Sensor and Actuator Networks
Matèries:	federated learning Internet of Things intrusion detection system deep learning data scaling DNN
Accés en línia:	https://www.mdpi.com/2224-2708/14/4/78
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