A nature-inspired approach to speed up optimum-path forest clustering and its application to intrusion detection in computer networks

Autor(es)

Costa, Kelton A. P. ^[1] ; Pereira, Luis A. M. ^[2] ; Nakamura, Rodrigo Y. M. ^[1] ; Pereira, Clayton R. ^[3] ; Papa, Joao P. ^[1] ; Falcao, Alexandre Xavier ^[2]

Afiliação do(s) autor(es)

^[1] Univ Estadual Paulista, Dept Comp, Bauru - Brazil

^[2] Univ Estadual Campinas, Inst Comp, Campinas - Brazil

^[3] Univ Fed Sao Carlos, Dept Comp, BR-13560 Sao Carlos, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: INFORMATION SCIENCES; v. 294, p. 95-108, FEB 10 2015.
• Citações Web of Science: 28

Resumo

We propose a nature-inspired approach to estimate the probability density function (pdf) used for data clustering based on the optimum-path forest algorithm (OPFC). OPFC interprets a dataset as a graph, whose nodes are the samples and each sample is connected to its k-nearest neighbors in a given feature space (a k-nn graph). The nodes of the graph are weighted by their pdf values and the pdf is computed based on the distances between the samples and their k-nearest neighbors. Once the k-nn graph is defined, OPFC finds one sample (root) at each maximum of the pdf and propagates one optimum-path tree (cluster) from each root to the remaining samples of its dome. Clustering effectiveness will depend on the pdf estimation, and the proposed approach efficiently computes the best value of k for a given application. We validate our approach in the context of intrusion detection in computer networks. First, we compare OPFC with data clustering based on k-means, and self-organization maps. Second, we evaluate several metaheuristic techniques to find the best value of k. (C) 2014 Elsevier Inc. All rights reserved. (AU)

• Processo FAPESP: 10/02045-3 - Detecção de Intrusões Baseada em Floresta de Caminhos Ótimos
• Beneficiário: Clayton Reginaldo Pereira
• Modalidade de apoio: Bolsas no Brasil - Mestrado
• Processo FAPESP: 11/14094-1 - Explorando Abordagens de Múltiplos Rótulos por Floresta de Caminhos Ótimos
• Beneficiário: Luis Augusto Martins Pereira
• Modalidade de apoio: Bolsas no Brasil - Mestrado
• Processo FAPESP: 09/16206-1 - Novas tendências em reconhecimento de padrões baseado em floresta de caminhos ótimos
• Beneficiário: João Paulo Papa
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores
• Processo FAPESP: 11/14058-5 - Explorando Abordagens de Aprendizado Sequencial para Floresta de Caminhos Ótimos
• Beneficiário: Rodrigo Yuji Mizobe Nakamura
• Modalidade de apoio: Bolsas no Brasil - Mestrado
• Processo FAPESP: 13/20387-7 - Otimização de hiperparâmetros em arquiteturas de aprendizado em profundidade
• Beneficiário: João Paulo Papa
• Modalidade de apoio: Bolsas no Exterior - Pesquisa