Telematika
Vol 14, No 2: August (2021)

Survey on Deep Learning Based Intrusion Detection System

Omar Muhammad Altoumi Alsyaibani (Universitas AMIKOM Yogyakarta)
Ema Utami (Universitas AMIKOM Yogyakarta)
Anggit Dwi Hartanto (Universitas AMIKOM Yogyakarta)



Article Info

Publish Date
26 Aug 2021

Abstract

Development of computer network has changed human lives in many ways. Currently, everyone is connected to each other from everywhere. Information can be accessed easily. This massive development has to be followed by good security system. Intrusion Detection System is important device in network security which capable of monitoring hardware and software in computer network. Many researchers have developed Intrusion Detection System continuously and have faced many challenges, for instance: low detection of accuracy, emergence of new types malicious traffic and error detection rate. Researchers have tried to overcome these problems in many ways, one of them is using Deep Learning which is a branch of Machine Learning for developing Intrusion Detection System and it will be discussed in this paper. Machine Learning itself is a branch of Artificial Intelligence which is growing rapidly in the moment. Several researches have showed that Machine Learning and Deep Learning provide very promising results for developing Intrusion Detection System. This paper will present an overview about Intrusion Detection System in general, Deep Learning model which is often used by researchers, available datasets and challenges which will be faced ahead by researchers

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Journal Info

Abbrev

TELEMATIKA

Publisher

Subject

Education

Description

Jl. Letjend Pol. Soemarto No.126, Watumas, Purwanegara, Kec. Purwokerto Utara, Kabupaten Banyumas, Jawa Tengah ...