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oai:gredos.usal.es:10366/1343512025-04-30T20:37:14Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134243

Sánchez, Raúl Herrero Cosío, Álvaro Corchado Rodríguez, Emilio Santiago 2017-09-05T11:01:22Z 2017-09-05T11:01:22Z 2013 Cybernetics and Systems. Volumen 44 (6-7), pp. 505-532. Informa UK Limited. 0196-9722 (Print) / 1087-6553 (Online) http://hdl.handle.net/10366/134351 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. application/pdf en Informa UK Limited Attribution-NonCommercial-NoDerivs 3.0 Unported https://creativecommons.org/licenses/by-nc-nd/3.0/ info:eu-repo/semantics/openAccess Computer Science Visualizationi and clustering for SNMP intrusion detection info:eu-repo/semantics/article