Multiobjective evolutionary clustering approach to security vulnerability assesments

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

6 Cites (Scopus)

Resum

Network vulnerability assessments collect large amounts of data to be further analyzed by security experts. Data mining and, particularly, unsupervised learning can help experts analyze these data and extract several conclusions. This paper presents a contribution to mine data in this security domain. We have implemented an evolutionary multiobjective approach to cluster data of security assessments. Clusters hold groups of tested devices with similar vulnerabilities to detect hidden patterns. Two different metrics have been selected as objectives to guide the discovery process. The results of this contribution are compared with other single-objective clustering approaches to confirm the value of the obtained clustering structures.

Idioma originalAnglès
Títol de la publicacióHybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings
Pàgines597-604
Nombre de pàgines8
DOIs
Estat de la publicacióPublicada - 2009
Esdeveniment4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009 - Salamanca, Spain
Durada: 10 de juny 200912 de juny 2009

Sèrie de publicacions

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volum5572 LNAI
ISSN (imprès)0302-9743
ISSN (electrònic)1611-3349

Conferència

Conferència4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009
País/TerritoriSpain
CiutatSalamanca
Període10/06/0912/06/09

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