Federated Intrusion Detection in Medical IoT: Client-Side Feature Learning with Variational Autoencoders vs Autoencoders

Authors

Kamal Singh (ORCID: https://orcid.org/0000-0002-5451-9751)
Guillaume Müller (ORCID: https://orcid.org/0000-0001-7110-039X)
David Durand (ORCID: https://orcid.org/0000-0001-8086-8886)
Gil Utard (ORCID: https://orcid.org/0000-0003-3081-6185)
Cyril Drocourt (ORCID: https://orcid.org/0000-0003-1636-9462)
Ahlem Harhad

Institutions

Mines Saint-Étienne (FR)
Laboratoire de Recherche en Informatique (FR)
Université de Picardie Jules Verne (FR)
Maulana Azad National Institute of Technology (IN)

Publication Details

Journal: SPIRE - Sciences Po Institutional REpository
Published: 2025-09-08
Primary Topic: Network Security and Intrusion Detection
Type: article

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article

Federated Intrusion Detection in Medical IoT: Client-Side Feature Learning with Variational Autoencoders vs Autoencoders

Kamal Singh, Guillaume Müller, David Durand, Gil Utard et al.

Sep 8, 2025

SPIRE - Sciences Po Institutional REpository

Network Security and Intrusion Detection

article

Federated Intrusion Detection in Medical IoT: Client-Side Feature Learning with Variational Autoencoders vs Autoencoders

Kamal Singh, Guillaume Müller, David Durand, Gil Utard, Cyril Drocourt, Ahlem Harhad

September 8, 2025article en

Abstract

No abstract available for this paper.

SPIRE - Sciences Po Institutional REpository

Mines Saint-Étienne (FR), Laboratoire de Recherche en Informatique (FR), Université de Picardie Jules Verne (FR), Maulana Azad National Institute of Technology (IN)

Network Security and Intrusion Detection

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