Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource, 1 online resource.

Language: Englisch

Bibliographic citation: Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset ; volume:6 ; number:1 ; day:5 ; month:9 ; year:2023 ; pages:1-15 ; date:12.2023
Cybersecurity ; 6, Heft 1 (5.9.2023), 1-15, 12.2023

Creator: Sharmila, B S.
Nagapadma, Rohini

Contributor: SpringerLink (Online service)

DOI: 10.1186/s42400-023-00178-5

URN: urn:nbn:de:101:1-2023102516195157822650

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:47 AM CEST

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Sharmila, B S.
Nagapadma, Rohini
SpringerLink (Online service)

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Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset

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