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Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT

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Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT

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Lopez-Martin, M.; Carro, B.; Sánchez-Esguevillas, A.; Lloret, J. (2017). Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT. Sensors. 17(9):1-17. https://doi.org/10.3390/s17091967

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/121260

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Title: Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Issued date:
Abstract:
[EN] The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host's network. In current networks, such systems are becoming more important as the ...[+]
Subjects: Intrusion detection , Variational methods , Conditional variational autoencoder , Feature recovery , Neural networks
Copyrigths: Reconocimiento (by)
Source:
Sensors. (eissn: 1424-8220 )
DOI: 10.3390/s17091967
Publisher:
MDPI AG
Publisher version: http://doi.org/10.3390/s17091967
Thanks:
This work has been partially funded by the Ministerio de Economia y Competitividad del Gobierno de Espana and the Fondo de Desarrollo Regional (FEDER) within the project "Inteligencia distribuida para el control y adaptacion ...[+]
Type: Artículo

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