@inproceedings{e297d3e178af47b68e67c7f751178f49,
title = "Data Mining Implementation for Monitoring Network Intrusion",
abstract = "The Information and Communication Network Center (BJIK) is one of the centers in the Agency for the Assessment and Application of Technology (BPPT). BJIK develops a network monitoring information system called Simontik to protect the BPPT system from threats where antivirus softwares and firewalls fail to give the level of protection needed. The random nature of threats makes it difficult to develop a rule-based system to predict the existence of intrusion. In this research, we apply a deep learning model to predict network intrusion. We found that our deep learning model using deep neural network and random forest algorithm can produce 99.91% accuracy compared to 98.11% using support vector machine algorithm.",
keywords = "data mining, deep learning, KDD, random forest, support vector machine",
author = "Annisa Andarrachmi and Wibowo, {Wahyu Catur}",
year = "2019",
month = oct,
doi = "10.1109/ICICoS48119.2019.8982408",
language = "English",
series = "ICICOS 2019 - 3rd International Conference on Informatics and Computational Sciences: Accelerating Informatics and Computational Research for Smarter Society in The Era of Industry 4.0, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICICOS 2019 - 3rd International Conference on Informatics and Computational Sciences",
address = "United States",
note = "3rd International Conference on Informatics and Computational Sciences, ICICOS 2019 ; Conference date: 29-10-2019 Through 30-10-2019",
}