Dataset: https://drive.google.com/drive/folders/1OgDTdg53oZp2ckDLNKoK4olmok6Wp6_y?usp=sharing
@INPROCEEDINGS{Luon2011:DDoS,
AUTHOR="Tan Khang Luong and Trung Dung Tran and Thanh Le",
TITLE="{DDoS} Attack Detection and Defense in {SDN} Based on Machine Learning",
BOOKTITLE="2020 7th NAFOSTED Conference on Information and Computer Science (NICS)
(NICS'20)",
ADDRESS="Ho Chi Minh City, Vietnam",
DAYS=25,
MONTH=nov,
YEAR=2020,
ABSTRACT="Distributed Denial of Service (DDoS) attack is one of the most dangerous
threats in computer networks. Hence, DDoS attack detection is one of the
key defense mechanisms. In this paper, we propose a DDoS detection and
defense approach in Software Defined Network (SDN) systems based on machine
learning (ML) and deep neural network (DNN) models. The combination of ML
and DNN classifiers with the centralized factors of SDN can efficiently
mitigate the harmful effect of DDoS to the network system. Besides, we
conducted two types of attack scenarios, one is from inside and one is from
outside of the network system."
}