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HH-NIDS: Heterogeneous Hardware-Based Network Intrusion Detection Framework for IoT Security

This study proposes a heterogeneous hardware-based framework for network intrusion detection using lightweight artificial neural network models. With the increase in the volume of exchanged data, IoT networks’ security has become a crucial issue. Anomaly-based intrusion detection systems (IDS) using...

Täydet tiedot

Tallennettuna:
Päätekijät: Duc-Minh Ngo, Dominic Lightbody, Andriy Temko, Cuong Pham-Quoc, Ngoc-Thinh Tran, Colin C. Murphy, Emanuel Popovici
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: MDPI AG 2022-12-01
Sarja:Future Internet
Aiheet:
network security
artificial neural Networks
hardware accelerators
low power
high-performance
microcontrollers
Linkit:https://www.mdpi.com/1999-5903/15/1/9
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