RT info:eu-repo/semantics/article
T1 Visualization and clustering for SNMP intrusion detection
A1 Sánchez, Raúl
A1 Herrero Cosío, Álvaro
A1 Corchado, Emilio
K1 Automatic response
K1 Clustering
K1 Computational intelligence
K1 Exploratory projection pursuit
K1 k-means
K1 Network intrusion detection
K1 Informática
K1 Computer science
AB Accurate intrusion detection is still an open challenge. The present work aims at being one step toward that purpose by studying the combination of clustering and visualization techniques. To do that, the mobile visualization connectionist agent-based intrusion detection system (MOVICAB-IDS), previously proposed as a hybrid intelligent IDS based on visualization techniques, is upgraded by adding automatic response thanks to clustering methods. To check the validity of the proposed clustering extension, it has been applied to the identification of different anomalous situations related to the simple network management network protocol by using real-life data sets. Different ways of applying neural projection and clustering techniques are studied in the present article. Through the experimental validation it is shown that the proposed techniques could be compatible and consequently applied to a continuous network flow for intrusion detection
PB Taylor & Francis
SN 0196-9722
YR 2013
FD 2013-10
LK http://hdl.handle.net/10259/3859
UL http://hdl.handle.net/10259/3859
LA eng
NO Spanish Ministry of Economy and Competitiveness with ref: TIN2010-21272-C02-01 (funded by the European Regional Development Fund) and SA405A12-2 from Junta de Castilla y Leon.
DS Repositorio Institucional de la Universidad de Burgos
RD 18-abr-2024