Unsupervised Visualization of SQL Attacks by Means of the SCMAS Architecture

  • Álvaro Herrero
  • Cristian I. Pinzón
  • Emilio Corchado
  • Javier Bajo
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 71)


This paper presents an improvement of the SCMAS architecture aimed at securing SQL-run databases. The main goal of such architecture is the detection and prevention of SQL injection attacks. The improvement consists in the incorporation of unsupervised projection models for the visual inspection of SQL traffic. Through the obtained projections, SQL injection queries can be identified and subsequent actions can be taken. The proposed approach has been tested on a real dataset, and the obtained results are shown.


Multiagent System for Security Neural Projection Models Unsupervised Learning Database Security SQL Injection Attacks 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Álvaro Herrero
    • 1
  • Cristian I. Pinzón
    • 2
  • Emilio Corchado
    • 2
  • Javier Bajo
    • 2
  1. 1.Civil Engineering DepartmentUniversity of BurgosBurgosSpain
  2. 2.Departamento de Informática y AutomáticaUniversidad de SalamancaSalamancaSpain

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