CBRid4SQL: A CBR Intrusion Detector for SQL Injection Attacks
One of the most serious security threats to recently deployed databases has been the SQL Injection attack. This paper presents an agent specialised in the detection of SQL injection attacks. The agent incorporates a Case-Based Reasoning engine which is equipped with a learning and adaptation capacit...
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| Other Authors: | , , , |
| Format: | article |
| Language: | English |
| Published: |
2018
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| Online Access: | http://ridda2.utp.ac.pa/handle/123456789/4783 |
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| _version_ | 1869451830966091776 |
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| author | Pinzón Trejos, Cristian |
| author2 | Herrero, Álvaro De Paz, Juan Corchado, Emilio Bajo, Javier |
| author2_role | author author author author |
| author_browse | Bajo, Javier Corchado, Emilio De Paz, Juan Herrero, Álvaro Pinzón Trejos, Cristian |
| author_facet | Pinzón Trejos, Cristian Herrero, Álvaro De Paz, Juan Corchado, Emilio Bajo, Javier |
| author_role | author |
| collection | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| dc.creator.none.fl_str_mv | Pinzón Trejos, Cristian Herrero, Álvaro De Paz, Juan Corchado, Emilio Bajo, Javier |
| dc.date.none.fl_str_mv | 06/23/2010 06/23/2010 2018-06-05T19:20:00Z 2018-06-05T19:20:00Z |
| dc.format.none.fl_str_mv | application/pdf application/pdf |
| dc.identifier.none.fl_str_mv | http://ridda2.utp.ac.pa/handle/123456789/4783 |
| dc.language.none.fl_str_mv | eng eng |
| dc.rights.none.fl_str_mv | https://creativecommons.org/licenses/by-nc-sa/4.0/ info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:Repositorio Institucional de documento digitales de acceso abierto de la UTP instname:Universidad Tecnológica de Panamá instacron:U Tecnológica de Panamá |
| dc.subject.none.fl_str_mv | SQL Injection Intrusion Detection CBR SVM Neural Networks SQL Injection Intrusion Detection CBR SVM Neural Networks |
| dc.title.none.fl_str_mv | CBRid4SQL: A CBR Intrusion Detector for SQL Injection Attacks |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | One of the most serious security threats to recently deployed databases has been the SQL Injection attack. This paper presents an agent specialised in the detection of SQL injection attacks. The agent incorporates a Case-Based Reasoning engine which is equipped with a learning and adaptation capacity for the classification of malicious codes. The agent also incorporates advanced algorithms in the reasoning cycle stages. The reuse phase uses an innovative classification model based on a mixture of a neuronal network together with a Support Vector Machine in order to classify the received SQL queries in the most reliable way. Finally, a visualisation neural technique is incorporated, which notably eases the revision stage carried out by human experts in the case of suspicious queries. The Classifier Agent was tested in a real-traffic case study and its experimental results, which validate the performance of the proposed approach, are presented here. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | PA_0d2a8684117b2586d61816dbbcb815cf |
| instacron_str | U Tecnológica de Panamá |
| institution | U Tecnológica de Panamá |
| instname_str | Universidad Tecnológica de Panamá |
| language | eng |
| network_acronym_str | PA |
| network_name_str | oai la ref anni2 |
| oai_identifier_str | oai:ridda2.utp.ac.pa:123456789/4783 |
| publishDate | 2018 |
| publishDateSort | 2018 |
| reponame_str | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | https://creativecommons.org/licenses/by-nc-sa/4.0/ |
| spelling | CBRid4SQL: A CBR Intrusion Detector for SQL Injection AttacksPinzón Trejos, CristianHerrero, ÁlvaroDe Paz, JuanCorchado, EmilioBajo, JavierSQL InjectionIntrusion DetectionCBRSVMNeural NetworksSQL InjectionIntrusion DetectionCBRSVMNeural NetworksOne of the most serious security threats to recently deployed databases has been the SQL Injection attack. This paper presents an agent specialised in the detection of SQL injection attacks. The agent incorporates a Case-Based Reasoning engine which is equipped with a learning and adaptation capacity for the classification of malicious codes. The agent also incorporates advanced algorithms in the reasoning cycle stages. The reuse phase uses an innovative classification model based on a mixture of a neuronal network together with a Support Vector Machine in order to classify the received SQL queries in the most reliable way. Finally, a visualisation neural technique is incorporated, which notably eases the revision stage carried out by human experts in the case of suspicious queries. The Classifier Agent was tested in a real-traffic case study and its experimental results, which validate the performance of the proposed approach, are presented here.One of the most serious security threats to recently deployed databases has been the SQL Injection attack. This paper presents an agent specialised in the detection of SQL injection attacks. The agent incorporates a Case-Based Reasoning engine which is equipped with a learning and adaptation capacity for the classification of malicious codes. The agent also incorporates advanced algorithms in the reasoning cycle stages. The reuse phase uses an innovative classification model based on a mixture of a neuronal network together with a Support Vector Machine in order to classify the received SQL queries in the most reliable way. Finally, a visualisation neural technique is incorporated, which notably eases the revision stage carried out by human experts in the case of suspicious queries. The Classifier Agent was tested in a real-traffic case study and its experimental results, which validate the performance of the proposed approach, are presented here.2018-06-05T19:20:00Z2018-06-05T19:20:00Z06/23/201006/23/2010info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://ridda2.utp.ac.pa/handle/123456789/4783engenghttps://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccessreponame:Repositorio Institucional de documento digitales de acceso abierto de la UTPinstname:Universidad Tecnológica de Panamáinstacron:U Tecnológica de Panamáoai:ridda2.utp.ac.pa:123456789/47832021-07-06T15:35:05Z |
| spellingShingle | CBRid4SQL: A CBR Intrusion Detector for SQL Injection Attacks Pinzón Trejos, Cristian SQL Injection Intrusion Detection CBR SVM Neural Networks SQL Injection Intrusion Detection CBR SVM Neural Networks |
| status_str | publishedVersion |
| title | CBRid4SQL: A CBR Intrusion Detector for SQL Injection Attacks |
| title_full | CBRid4SQL: A CBR Intrusion Detector for SQL Injection Attacks |
| title_fullStr | CBRid4SQL: A CBR Intrusion Detector for SQL Injection Attacks |
| title_full_unstemmed | CBRid4SQL: A CBR Intrusion Detector for SQL Injection Attacks |
| title_short | CBRid4SQL: A CBR Intrusion Detector for SQL Injection Attacks |
| title_sort | CBRid4SQL: A CBR Intrusion Detector for SQL Injection Attacks |
| topic | SQL Injection Intrusion Detection CBR SVM Neural Networks SQL Injection Intrusion Detection CBR SVM Neural Networks |
| url | http://ridda2.utp.ac.pa/handle/123456789/4783 |