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An Adaptive Mechanism to Protect Databases against SQL Injection

The purpose of this article is to present an adaptive and intelligent mechanism that can handle SQL injection attacks. This proposal focuses on integrating a case-based reasoning (CBR) mechanism with a neural network. The proposed solution thus adapts to changes in attack patterns and provides the...

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Autores Principales: Pinzón Trejos, Cristian, De Paz, Juan, Bajo, Javier, Corchado, Juan
Formato: Artículo
Idioma: Inglés
Inglés
Publicado: 2018
Materias:
SQL Injection
database security
case-based reasoning
neural network
Acceso en línea: http://ridda2.utp.ac.pa/handle/123456789/4893
http://ridda2.utp.ac.pa/handle/123456789/4893
id RepoUTP4893
recordtype dspace
spelling RepoUTP48932021-07-06T15:35:07Z An Adaptive Mechanism to Protect Databases against SQL Injection Pinzón Trejos, Cristian De Paz, Juan Bajo, Javier Corchado, Juan SQL Injection database security case-based reasoning neural network SQL Injection database security case-based reasoning neural network The purpose of this article is to present an adaptive and intelligent mechanism that can handle SQL injection attacks. This proposal focuses on integrating a case-based reasoning (CBR) mechanism with a neural network. The proposed solution thus adapts to changes in attack patterns and provides the ability to detect attacks independently of their evolution. A prototype of the architecture was developed and the results obtained are presented in this study. The purpose of this article is to present an adaptive and intelligent mechanism that can handle SQL injection attacks. This proposal focuses on integrating a case-based reasoning (CBR) mechanism with a neural network. The proposed solution thus adapts to changes in attack patterns and provides the ability to detect attacks independently of their evolution. A prototype of the architecture was developed and the results obtained are presented in this study. 2018-06-11T19:01:23Z 2018-06-11T19:01:23Z 2018-06-11T19:01:23Z 2018-06-11T19:01:23Z 2015-07-01 2015-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://ridda2.utp.ac.pa/handle/123456789/4893 http://ridda2.utp.ac.pa/handle/123456789/4893 eng eng https://creativecommons.org/licenses/by-nc-sa/4.0/ info:eu-repo/semantics/openAccess application/pdf application/pdf
institution Universidad Tecnológica de Panamá
collection Repositorio UTP – Ridda2
language Inglés
Inglés
topic SQL Injection
database security
case-based reasoning
neural network
SQL Injection
database security
case-based reasoning
neural network
spellingShingle SQL Injection
database security
case-based reasoning
neural network
SQL Injection
database security
case-based reasoning
neural network
Pinzón Trejos, Cristian
De Paz, Juan
Bajo, Javier
Corchado, Juan
An Adaptive Mechanism to Protect Databases against SQL Injection
description The purpose of this article is to present an adaptive and intelligent mechanism that can handle SQL injection attacks. This proposal focuses on integrating a case-based reasoning (CBR) mechanism with a neural network. The proposed solution thus adapts to changes in attack patterns and provides the ability to detect attacks independently of their evolution. A prototype of the architecture was developed and the results obtained are presented in this study.
format Artículo
author Pinzón Trejos, Cristian
De Paz, Juan
Bajo, Javier
Corchado, Juan
author_sort Pinzón Trejos, Cristian
title An Adaptive Mechanism to Protect Databases against SQL Injection
title_short An Adaptive Mechanism to Protect Databases against SQL Injection
title_full An Adaptive Mechanism to Protect Databases against SQL Injection
title_fullStr An Adaptive Mechanism to Protect Databases against SQL Injection
title_full_unstemmed An Adaptive Mechanism to Protect Databases against SQL Injection
title_sort adaptive mechanism to protect databases against sql injection
publishDate 2018
url http://ridda2.utp.ac.pa/handle/123456789/4893
http://ridda2.utp.ac.pa/handle/123456789/4893
_version_ 1796210199652990976
score 12.043282

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