Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource, 1 online resource.
- Sprache
-
Englisch
- Erschienen in
-
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
- Urheber
-
Sharmila, B S.
Nagapadma, Rohini
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s42400-023-00178-5
- URN
-
urn:nbn:de:101:1-2023102516195157822650
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:47 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Sharmila, B S.
- Nagapadma, Rohini
- SpringerLink (Online service)
Ähnliche Objekte (12)
Enhanced IoMT security framework using group teaching optimized auto-encoder for intrusion detection
Anomaly detection scheme for lung CT images using vector quantized variational auto-encoder with support vector data description
Smartwatch-Based IoT Fall Detection Application
Drowsy Driving Detection System – IoT Perspective
Attention-based residual autoencoder for video anomaly detection
AN EXPLAINABLE CONVOLUTIONAL AUTOENCODER MODEL FOR UNSUPERVISED CHANGE DETECTION
Anomaly detection in facial skin temperature using variational autoencoder
Deep autoencoder for false positive reduction in handgun detection
N-IoU: better IoU-based bounding box regression loss for object detection
Anomaly-based intrusion detection system for IoT application
Intelligent hyperspectral target detection for reliable IoV applications
Towards Objective Comparison of Security Algorithms for Resource-Constrained IoT Devices
Enhanced IoMT security framework using group teaching optimized auto-encoder for intrusion detection
Anomaly detection scheme for lung CT images using vector quantized variational auto-encoder with support vector data description
Smartwatch-Based IoT Fall Detection Application
Drowsy Driving Detection System – IoT Perspective
Attention-based residual autoencoder for video anomaly detection
AN EXPLAINABLE CONVOLUTIONAL AUTOENCODER MODEL FOR UNSUPERVISED CHANGE DETECTION
Anomaly detection in facial skin temperature using variational autoencoder
Deep autoencoder for false positive reduction in handgun detection
N-IoU: better IoU-based bounding box regression loss for object detection
Anomaly-based intrusion detection system for IoT application
Intelligent hyperspectral target detection for reliable IoV applications
Towards Objective Comparison of Security Algorithms for Resource-Constrained IoT Devices
Enhanced IoMT security framework using group teaching optimized auto-encoder for intrusion detection
Anomaly detection scheme for lung CT images using vector quantized variational auto-encoder with support vector data description
Smartwatch-Based IoT Fall Detection Application
Drowsy Driving Detection System – IoT Perspective
Attention-based residual autoencoder for video anomaly detection
AN EXPLAINABLE CONVOLUTIONAL AUTOENCODER MODEL FOR UNSUPERVISED CHANGE DETECTION
Anomaly detection in facial skin temperature using variational autoencoder
Deep autoencoder for false positive reduction in handgun detection
N-IoU: better IoU-based bounding box regression loss for object detection
Anomaly-based intrusion detection system for IoT application
Intelligent hyperspectral target detection for reliable IoV applications