Detect botnet attacks traffic using long shorts term memory technique

Muna Mohammad Taher Jawhar, Maha Abd Alalla Mohammad

Abstract


The spread of the internet of things (IoT) greatly are to its targeting by other parties that are considered suspicious or malicious, such as the attacks that are exposed to various networks to endanger their security. For this reason, it was necessary to take strict measures to protect the security and stability of networks in general and the internet of things in particular. It is worth noting that the current study presented a model and chose a long shorts term memory (LSTM) for attack detection through the use of deep learning technology via Keywords: the internet of things as well as the detection of bots in IoT systems.

Keywords


Botnet; Cybersecurity; Internet of things; Long shorts term memory; Network attacks

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DOI: http://doi.org/10.11591/ijeecs.v31.i1.pp400-405

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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