KJCKorea
Journal Central

@article{ART002789930},
author={Koohong Kang},
title={A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2021},
volume={26},
number={12},
pages={123-132},
doi={10.9708/jksci.2021.26.12.123}

TY - JOUR
AU - Koohong Kang
TI - A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic
JO - Journal of The Korea Society of Computer and Information
PY - 2021
VL - 26
IS - 12
PB - The Korean Society Of Computer And Information
SP - 123
EP - 132
SN - 1598-849X
AB - Malicious activities of Botnets are responsible for huge financial losses to Internet Service Providers, companies, governments and even home users. In this paper, we try to confirm the possibility of detecting botnet traffic by applying the deep learning model Convolutional Neural Network (CNN) using the CTU-13 botnet traffic dataset. In particular, we classify three classes, such as the C&C traffic between bots and C&C servers to detect C&C servers, traffic generated by bots other than C&C communication to detect bots, and normal traffic. Performance metrics were presented by accuracy, precision, recall, and F1 score on classifying both known and unknown botnet traffic. Moreover, we propose a stackable botnet detection system that can load modules for each botnet type considering scalability and operability on the real field.
KW - Botnet;Botnet Detection System;Deep Learning;Convolutional Neural Network;CTU-13 Dataset
DO - 10.9708/jksci.2021.26.12.123
ER -

Koohong Kang. (2021). A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic. Journal of The Korea Society of Computer and Information, 26(12), 123-132.

Koohong Kang. 2021, "A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic", Journal of The Korea Society of Computer and Information, vol.26, no.12 pp.123-132. Available from: doi:10.9708/jksci.2021.26.12.123

Koohong Kang "A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic" Journal of The Korea Society of Computer and Information 26.12 pp.123-132 (2021) : 123.

Koohong Kang. A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic. 2021; 26(12), 123-132. Available from: doi:10.9708/jksci.2021.26.12.123

Koohong Kang. "A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic" Journal of The Korea Society of Computer and Information 26, no.12 (2021) : 123-132.doi: 10.9708/jksci.2021.26.12.123

Koohong Kang. A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic. Journal of The Korea Society of Computer and Information, 26(12), 123-132. doi: 10.9708/jksci.2021.26.12.123

Koohong Kang. A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic. Journal of The Korea Society of Computer and Information. 2021; 26(12) 123-132. doi: 10.9708/jksci.2021.26.12.123

Koohong Kang. A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic. 2021; 26(12), 123-132. Available from: doi:10.9708/jksci.2021.26.12.123

Koohong Kang. "A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic" Journal of The Korea Society of Computer and Information 26, no.12 (2021) : 123-132.doi: 10.9708/jksci.2021.26.12.123