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Fernández Villamor, José Ignacio and Garijo Ayestaran, Mercedes (2008). A machine learning approach with verification of predictions and assisted supervision for a rule-based network intrusion detection system. In: "WEBIST 2008: 4th International Conference on Web Information Systems and Technologies", 04/05/2008-07/05/2008, Funchal, Portugal. ISBN 978-989-8111-26-5.
Title: | A machine learning approach with verification of predictions and assisted supervision for a rule-based network intrusion detection system |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | WEBIST 2008: 4th International Conference on Web Information Systems and Technologies |
Event Dates: | 04/05/2008-07/05/2008 |
Event Location: | Funchal, Portugal |
Title of Book: | WEBIST 2008: Proceedings of the 4th International Conference on Web Information Systems and Technologies |
Date: | 2008 |
ISBN: | 978-989-8111-26-5 |
Subjects: | |
Freetext Keywords: | Network Intrusion Detection Systems, Rules of inference, Machine learning, Decision trees, Self-organizing maps |
Faculty: | E.T.S.I. Telecomunicación (UPM) |
Department: | Ingeniería de Sistemas Telemáticos |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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Network security is a branch of network management in which network intrusion detection systems provide attack detection features by monitorization of traffic data. Rule-based misuse detection systems use a set of rules or signatures to detect attacks that exploit a particular vulnerability. These rules have to be handcoded by experts to properly identify vulnerabilities, which results in misuse detection systems having limited extensibility. This paper proposes a machine learning layer on top of a rule-based misuse detection system that provides automatic generation of detection rules, prediction verification and assisted classification of new data. Our system offers an overall good performance, while adding an heuristic and adaptive approach to existing rule-based misuse detection systems.
Item ID: | 4109 |
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DC Identifier: | https://oa.upm.es/4109/ |
OAI Identifier: | oai:oa.upm.es:4109 |
Official URL: | http://www.webist.org/WEBIST2008/index.htm |
Deposited by: | Memoria Investigacion |
Deposited on: | 14 Sep 2010 11:38 |
Last Modified: | 20 Apr 2016 13:27 |