Detail publikace

SVM Algorithm Training for DDoS on SDN Networks

SHUJAIRI, M. ŠKORPIL, V.

Originální název

SVM Algorithm Training for DDoS on SDN Networks

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Despite the flexibility provided by SDN technology is also vulnerable to attacks such as DDoS attacks, Network DDoS attack is a serious threat to the Internet today because internet traffic is increasing day by day, it is difficult to distinguish between legitimate and malicious traffic. To alleviate the DDoS attack in the campus network, to mitigate this attack, propose in this paper to classify benign traffic from DDoS attack traffic by SVM of the classification algorithms based on machine learning. As the contribution of this paper is to train the SVM algorithm which has been used in the approach for the training process. Due to the complexity of the dataset, using a type of kernel called a polynomial kernel to accomplish non-linearity discriminative. The results showed that the traffic classification was with the highest accuracy 96 %

Klíčová slova

SDN, ML, SVM, RYU, DDoS

Autoři

SHUJAIRI, M.; ŠKORPIL, V.

Vydáno

26. 4. 2022

Nakladatel

Brno university of technology, Faculty of Electronic Engineering and Communication

Místo

Brno

ISBN

978-80-214-6029-4

Kniha

Proceedings of the 28 Conference STUDENT EEICT 2022 General papers

Edice

1

Strany od

475

Strany do

479

Strany počet

5

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1_v2.pdf

BibTex

@inproceedings{BUT177743,
  author="Murtadha Mohsin Hadi {Shujairi} and Vladislav {Škorpil}",
  title="SVM Algorithm Training for DDoS on SDN Networks",
  booktitle="Proceedings of the 28 Conference STUDENT EEICT 2022 General papers",
  year="2022",
  series="1",
  pages="475--479",
  publisher="Brno university of technology, Faculty of Electronic Engineering and Communication",
  address="Brno",
  isbn="978-80-214-6029-4",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1_v2.pdf"
}