Comparative Analysis between the k-means and Fuzzy c-means Algorithms to Detect UDP Flood DDoS Attack on a SDN/NFV Environment

João Neto, Layse Souza, Admilson Ribeiro

2020

Abstract

Distributed Denial of Service (DDoS) attacks are a growing issue for computer networks security and have become a serious network security problem. Environments based on Software Defined Networking (SDN) and Network Function Virtualization (NFV) offers the ability to program a network and allows dynamic creation of flow policies. Allied to that, clustering algorithms can be used to classify and detect DDoS. This paper presents a study and an analysis of two unsupervised machine learning algorithms used to detect DDoS attacks in an SDN/NFV simulated environment. The results obtained by the two algorithms include an accuracy rate of 99% and the k-means algorithm was 33% faster than fuzzy c-means, which demonstrates its effectiveness and scalability.

Paper Citation

in Harvard Style

Neto J., Souza L. and Ribeiro A. (2020). Comparative Analysis between the k-means and Fuzzy c-means Algorithms to Detect UDP Flood DDoS Attack on a SDN/NFV Environment.In Proceedings of the 16th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-478-7, pages 105-112. DOI: 10.5220/0010176201050112

in Bibtex Style

@conference{webist20,
author={João Neto and Layse Souza and Admilson Ribeiro},
title={Comparative Analysis between the k-means and Fuzzy c-means Algorithms to Detect UDP Flood DDoS Attack on a SDN/NFV Environment},
booktitle={Proceedings of the 16th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2020},
pages={105-112},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010176201050112},
isbn={978-989-758-478-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Comparative Analysis between the k-means and Fuzzy c-means Algorithms to Detect UDP Flood DDoS Attack on a SDN/NFV Environment
SN - 978-989-758-478-7
AU - Neto J.
AU - Souza L.
AU - Ribeiro A.
PY - 2020
SP - 105
EP - 112
DO - 10.5220/0010176201050112