📅 26 August 2021
DOI: 10.35671/telematika.v14i2.1317
Survey on Deep Learning Based Intrusion Detection System
Telematika
Universitas Amikom Purwokerto
📄 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
🔖 Keywords
#Deep Learning; IDS Research; IDS Review; Deep Learning Model; IDS Dataset
ℹ️ Informasi Publikasi
Tanggal Publikasi
26 August 2021
Volume / Nomor / Tahun
Volume 14, Nomor 2, Tahun 2021
📝 HOW TO CITE
Alsyaibani, Omar Muhammad Altoumi; Universitas AMIKOM Yogyakarta; Utami, Ema; Universitas AMIKOM Yogyakarta; Hartanto, Anggit Dwi; Universitas AMIKOM Yogyakarta; , "Survey on Deep Learning Based Intrusion Detection System," Telematika, vol. 14, no. 2, Aug. 2021.
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