Self-Organizing Maps for Early Detection of Denial of Service Attacks

  • Miguel Ángel Pérez del Pino
  • Patricio García Báez
  • Pablo Fernández López
  • Carmen Paz Suárez Araujo
Part of the Studies in Computational Intelligence book series (SCI, volume 378)


Detection and early alert of Denial of Service (DoS) attacks are very important actions to make appropriate decisions in order to minimize their negative impact. DoS attacks have been catalogued as of high-catastrophic index and hard to defend against. Our study presents advances in the area of computer security against DoS attacks. In this chapter, a flexible method is presented, capable of effectively tackling and overcoming the challenge of DoS (and distributed DoS) attacks using a CISDAD (Computer Intelligent System for DoS Attacks Detection). It is a hybrid intelligent system with a modular structure: a pre-processing module (non neural) and a processing module based on Kohonen Self-Organizing artificial neural networks. The proposed system introduces an automatic differential detection of several Normal Traffic and several Toxic Traffics, clustering them upon its Transport-Layer-Protocol behavior. Two computational studies of CISDAD working with real networking traffic will be described, showing a high level of effectiveness in the CISDAD detection process. Finally, in this chapter, the possibility for specific adaptation to the Healthcare environment that CISDAD can offer is introduced.


Legitimate User Transport Control Protocol Network Address Translation Service Attack Hybrid Intelligent System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Miguel Ángel Pérez del Pino
    • 1
  • Patricio García Báez
    • 2
  • Pablo Fernández López
    • 1
  • Carmen Paz Suárez Araujo
    • 1
  1. 1.Instituto Universitario de Ciencias y Tecnologas CibernéticasUniversidad de Las Palmas de Gran CanariaLas Palmas de Gran CanariaSpain
  2. 2.Departamento de Estadística, Investigación Operativa y ComputacónUniversidad de La LagunaLa LagunaSpain

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