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Authors: João Ribeiro de Almeida Neto ; Layse Santos Souza and Admilson de Ribamar Lima Ribeiro

Affiliation: Department of Computing, Federal University of Sergipe (UFS), São Cristóvão, Brazil

Keyword(s): Attack Detection, DDoS Attack, UDP Flooding, SDN, NFV, Microservices, Machine Learning, Fuzzy c-means, k-means.

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.

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Paper citation in several formats:
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 - WEBIST; ISBN 978-989-758-478-7; ISSN 2184-3252, SciTePress, pages 105-112. DOI: 10.5220/0010176201050112

@conference{webist20,
author={João Ribeiro de Almeida Neto. and Layse Santos Souza. and Admilson de Ribamar Lima 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 - WEBIST},
year={2020},
pages={105-112},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010176201050112},
isbn={978-989-758-478-7},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Web Information Systems and Technologies - 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
IS - 2184-3252
AU - Neto, J.
AU - Souza, L.
AU - Ribeiro, A.
PY - 2020
SP - 105
EP - 112
DO - 10.5220/0010176201050112
PB - SciTePress

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