RT-MOVICAB-IDS: Addressing real-time intrusion detection
| Autor: | Emilio Corchado, Álvaro Herrero, Vicente Julián, Martí Navarro |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Computer Networks and Communications
Network security Computer science Intrusion detection system Machine learning computer.software_genre Unsupervised learning Field (computer science) Hybrid Artificial Intelligent Systems Intrusion detection Case-based reasoning Time-bounded deliberative process Adaptation (computer science) Artificial Neural Networks Informática Artificial neural network business.industry Multi-Agent systems Multi-agent system Hardware and Architecture Artificial intelligence Computer network security business LENGUAJES Y SISTEMAS INFORMATICOS computer Software |
| Zdroj: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname Repositorio Institucional de la Universidad de Burgos (RIUBU) |
| ISSN: | 0167-739X 2010-2127 |
| Popis: | [EN] This study presents a novel Hybrid Intelligent Intrusion Detection System (IDS) known as RT-MOVICABIDS that incorporates temporal control. One of its main goals is to facilitate real-time Intrusion Detection, as accurate and swift responses are crucial in this field, especially if automatic abortion mechanisms are running. The formulation of this hybrid IDS combines Artificial Neural Networks (ANN) and Case-Based Reasoning (CBR) within a Multi-Agent System (MAS) to detect intrusions in dynamic computer networks. Temporal restrictions are imposed on this IDS, in order to perform real/execution time processing and assure system response predictability. Therefore, a dynamic real-time multi-agent architecture for IDS is proposed in this study, allowing the addition of predictable agents (both reactive and deliberative). In particular, two of the deliberative agents deployed in this system incorporate temporal-bounded CBR. This upgraded CBR is based on an anytime approximation, which allows the adaptation of this Artificial Intelligence paradigm to real-time requirements. Experimental results using real data sets are presented which validate the performance of this novel hybrid IDS. © 2011 Elsevier B.V. All rights reserved. This research is funded through the Junta of Castilla and León (BU006A08); the Spanish Ministry of Science and Innovation (TIN2010-21272-C02-01), Education and Innovation (CIT-020000-2008-2 and CIT-020000-2009-12); the Spanish government (TIN2009-13839-C03-01), FEDER and CONSOLIDER-INGENIO (2010 CSD2007-00022) and the Generalitat Valenciana (PROMETEO/ 2008/051). The authors would also like to thank the vehicle interior manufacturer, Grupo Antolin Ingenieria S.A. for supporting the project through the MAGNO2008 – 1028.– CENIT Project funded by the Spanish Ministry of Science and Innovation. |
| Databáze: | OpenAIRE |
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