IoT botnet attack detection using deep autoencoder and artificial neural networks
IoT botnet attack detection using deep autoencoder and artificial neural networks
About this item
Full title
Author / Creator
Publisher
KSII, the Korean Society for Internet Information
Journal title
Language
English
Formats
Publication information
Publisher
KSII, the Korean Society for Internet Information
Subjects
More information
Scope and Contents
Contents
As Internet of Things (IoT) applications and devices rapidly grow, cyber-attacks on IoT networks/systems also have an increasing trend, thus increasing the threat to security and privacy. Botnet is one of the threats that dominate the attacks as it can easily compromise devices attached to an IoT networks/systems. The compromised devices will behav...
Alternative Titles
Full title
IoT botnet attack detection using deep autoencoder and artificial neural networks
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_nrf_kci_oai_kci_go_kr_ARTI_10409143
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_nrf_kci_oai_kci_go_kr_ARTI_10409143
Other Identifiers
ISSN
1976-7277
E-ISSN
1976-7277
DOI
10.3837/tiis.2023.05.001
