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Reconocimiento de patrones para identificación de usuarios en accesos informáticos

Authors: Guevara Maldonado, César Byron;

Reconocimiento de patrones para identificación de usuarios en accesos informáticos

Abstract

La detección y control de intrusos o accesos no autorizados en los sistemas informáticos ha sido desde siempre un tema a tener en cuenta en los sistemas de información donde la seguridad, integridad y privacidad de la información son aspectos fundamentales. El avance del conocimiento y la tecnología es cada vez mayor, lo que permite el desarrollo y aplicación de sistemas informáticos más sofisticados y eficientes, pero también aumenta la posibilidad de que sean vulnerados mediante accesos no legítimos. En este trabajo se plantea el uso de diversas técnicas automáticas para identificar a los usuarios que acceden a datos fundamentales de los sistemas y comprobar si el acceso está o no permitido. Se han aplicado técnicas avanzadas e inteligentes para el análisis y aplicación de minería de datos, para obtener patrones de comportamiento; como son los árboles de decisión y las redes neuronales artificiales (RNA). Con ellas se obtienen perfiles dinámicos (patrones) de usuario. La hipótesis principal del trabajo es una solución efectiva para la detección de intrusos en los sistemas informáticos de información. [Abstract] The detection and control of intruders or unauthorized access to computer systems has always been an issue to consider in information systems where security, integrity and privacy of information are key issues. The advancement of knowledge and technology is getting greater, allowing the development and application of more sophisticated and efficient computer systems, but also increases the possibility of being violated by illegitimate accesses. The propose of this paper is to use different automated techniques to identify users accessing systems critical data, to check whether or not access is allowed. Advanced and intelligent analysis and application of data mining techniques have been applied for obtaining patterns of behavior, such as decision trees and artificial neural networks. Dynamic user profiles (patterns) are obtained with them. The main hypothesis of the work is an effective solution for the detection of intruders in computer information systems.

Country
Spain
Related Organizations
Keywords

Intrusión, 004.056(043.3), Accesos no legítimos, Perfil de comportamiento, Pattern Recognition, 004.492(043.3), Information Databases, Inteligencia artificial, Illegitimate Access, 1203.04 Inteligencia Artificial, Security, Inteligencia artificial (Informática), Behavioral Profile, 004.8(043.3), Bases de información, Seguridad, Detección intrusos. Intrusion, Detecting Intruders., Reconocimiento de patrones, Seguridad informática

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green