Traffic Based Sequential Learning During Botnet Attacks to Identify Compromised IoT Devices

A novel online Compromised Device Identification System (CDIS) is presented to identify IoT devices and/or IP addresses that are compromised by a Botnet attack, within a set of sources and destinations that transmit packets. The method uses specific metrics that are selected for this purpose and whi...

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Hlavní autoři:	Erol Gelenbe, Mert Nakip
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2022-01-01
Edice:	IEEE Access
Témata:	Internet of Things (IoT) compromised device identification random neural network auto-associative deep random neural network botnets Mirai
On-line přístup:	https://ieeexplore.ieee.org/document/9969594/
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