Strengthening intrusion detection techniques through emerging patterns
- Autores
- Grandinetti, Walter M.
- Año de publicación
- 2004
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- In todays world where nearly every company is dependent on the Internet to survive, it is not surprising that the role of intrusion detection has become extremely important within the last decade. Intrusion detection involves determining whether some entity has attempted to gain, or worse, it has gained unauthorized access to the system. The task of current intrusion detection systems is detect possible threats not only from insiders but also from outsiders. Based on our current knowledge, there are two things the system administrator could do in order to keep secure his system. First, use preventive measures. Second, make use of the audit logs. Due to the sheer volume of the logs, it is required that this task be performed automat- ically. Data Mining eld of study has help to partially automatize this process. However, the current state of art has still left too much to the administrator and sometimes it distract the administrator raising false alarms. This work propose to apply a new technique, successfully used in others elds of knowledge as Bioinformatics and Classi cation Systems, in order to de ne more accurately user's pro les and to detect more intruders, raising a lower number of false alarms and having a precision higher than other techniques.
Eje: Redes y arquitecturas
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
system security
pattern mining
emerging patterns
jumping emerging patterns
Patterns
Security
Software Architectures - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/21311
Ver los metadatos del registro completo
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Strengthening intrusion detection techniques through emerging patternsGrandinetti, Walter M.Ciencias Informáticassystem securitypattern miningemerging patternsjumping emerging patternsPatternsSecuritySoftware ArchitecturesIn todays world where nearly every company is dependent on the Internet to survive, it is not surprising that the role of intrusion detection has become extremely important within the last decade. Intrusion detection involves determining whether some entity has attempted to gain, or worse, it has gained unauthorized access to the system. The task of current intrusion detection systems is detect possible threats not only from insiders but also from outsiders. Based on our current knowledge, there are two things the system administrator could do in order to keep secure his system. First, use preventive measures. Second, make use of the audit logs. Due to the sheer volume of the logs, it is required that this task be performed automat- ically. Data Mining eld of study has help to partially automatize this process. However, the current state of art has still left too much to the administrator and sometimes it distract the administrator raising false alarms. This work propose to apply a new technique, successfully used in others elds of knowledge as Bioinformatics and Classi cation Systems, in order to de ne more accurately user's pro les and to detect more intruders, raising a lower number of false alarms and having a precision higher than other techniques.Eje: Redes y arquitecturasRed de Universidades con Carreras en Informática (RedUNCI)2004-05info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf546-551http://sedici.unlp.edu.ar/handle/10915/21311enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:27:25Zoai:sedici.unlp.edu.ar:10915/21311Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:27:25.938SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Strengthening intrusion detection techniques through emerging patterns |
title |
Strengthening intrusion detection techniques through emerging patterns |
spellingShingle |
Strengthening intrusion detection techniques through emerging patterns Grandinetti, Walter M. Ciencias Informáticas system security pattern mining emerging patterns jumping emerging patterns Patterns Security Software Architectures |
title_short |
Strengthening intrusion detection techniques through emerging patterns |
title_full |
Strengthening intrusion detection techniques through emerging patterns |
title_fullStr |
Strengthening intrusion detection techniques through emerging patterns |
title_full_unstemmed |
Strengthening intrusion detection techniques through emerging patterns |
title_sort |
Strengthening intrusion detection techniques through emerging patterns |
dc.creator.none.fl_str_mv |
Grandinetti, Walter M. |
author |
Grandinetti, Walter M. |
author_facet |
Grandinetti, Walter M. |
author_role |
author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas system security pattern mining emerging patterns jumping emerging patterns Patterns Security Software Architectures |
topic |
Ciencias Informáticas system security pattern mining emerging patterns jumping emerging patterns Patterns Security Software Architectures |
dc.description.none.fl_txt_mv |
In todays world where nearly every company is dependent on the Internet to survive, it is not surprising that the role of intrusion detection has become extremely important within the last decade. Intrusion detection involves determining whether some entity has attempted to gain, or worse, it has gained unauthorized access to the system. The task of current intrusion detection systems is detect possible threats not only from insiders but also from outsiders. Based on our current knowledge, there are two things the system administrator could do in order to keep secure his system. First, use preventive measures. Second, make use of the audit logs. Due to the sheer volume of the logs, it is required that this task be performed automat- ically. Data Mining eld of study has help to partially automatize this process. However, the current state of art has still left too much to the administrator and sometimes it distract the administrator raising false alarms. This work propose to apply a new technique, successfully used in others elds of knowledge as Bioinformatics and Classi cation Systems, in order to de ne more accurately user's pro les and to detect more intruders, raising a lower number of false alarms and having a precision higher than other techniques. Eje: Redes y arquitecturas Red de Universidades con Carreras en Informática (RedUNCI) |
description |
In todays world where nearly every company is dependent on the Internet to survive, it is not surprising that the role of intrusion detection has become extremely important within the last decade. Intrusion detection involves determining whether some entity has attempted to gain, or worse, it has gained unauthorized access to the system. The task of current intrusion detection systems is detect possible threats not only from insiders but also from outsiders. Based on our current knowledge, there are two things the system administrator could do in order to keep secure his system. First, use preventive measures. Second, make use of the audit logs. Due to the sheer volume of the logs, it is required that this task be performed automat- ically. Data Mining eld of study has help to partially automatize this process. However, the current state of art has still left too much to the administrator and sometimes it distract the administrator raising false alarms. This work propose to apply a new technique, successfully used in others elds of knowledge as Bioinformatics and Classi cation Systems, in order to de ne more accurately user's pro les and to detect more intruders, raising a lower number of false alarms and having a precision higher than other techniques. |
publishDate |
2004 |
dc.date.none.fl_str_mv |
2004-05 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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conferenceObject |
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publishedVersion |
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http://sedici.unlp.edu.ar/handle/10915/21311 |
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http://sedici.unlp.edu.ar/handle/10915/21311 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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