A nature-inspired approach to speed up optimum-path forest clustering and its application to intrusion detection in computer networks
type: Item
instance of: scholarly article
title: A nature-inspired approach to speed up optimum-path forest clustering and its application to intrusion detection in computer networks
zbMATH Open document ID: 1360.62323
author: Kelton A. P. Costa
author: Luis A. M. Pereira
author: Rodrigo Y. M. Nakamura
author: Clayton R. Pereira
author: Alexandre Falcao
author: João Paulo Papa
published in: Information Sciences
publication date: 2017-05-15T00:00:00Z
Mathematics Subject Classification ID: 62H30
zbMATH DE Number: 6715453
zbMATH Keywords: intrusion detection
zbMATH Keywords: optimum-path forest
zbMATH Keywords: meta-heuristic
zbMATH Keywords: clustering
describes a project that uses: KDD Cup
describes a project that uses: LibOPF
MaRDI profile type: Publication
full work available at URL: j.ins.2014.09.025
OpenAlex ID: W1996799478
cites work: Computational Science – ICCS 2005
cites work: Application of SVM and ANN for intrusion detection
cites work: Fundamentals of physics. Part I
cites work: Q4001920
cites work: GSA: A gravitational search algorithm
cites work: A New Metaheuristic Bat-Inspired Algorithm
DOI: 10.1016/J.INS.2014.09.025
description: scientific article; zbMATH DE number 6715453