Distributed network architecture in the detection of non content based attacks and insider intrusions with analogies taken from biological immune systems

Tesis: Tesis doctoral

Resumen

In order to analyze results of anomaly detection methods for Network Intrusion Detection Systems, the DARPA KDD dataset have been widely analyzed but their data are outdated for most kinds of attacks. A software called Spleen designed to get data from a tested network with the same structure of DARPA dataset is introduced. The application is used to complete the dataset with additional features according to an attack analysis. Finally, to show advantages of an extended dataset, two genetic methods in the detection of non-content based attacks are tested
Fecha de lectura25 jul. 2011
Idioma originalEspañol
Institución de lectura
  • Pontificia Universidad Javeriana

Palabras clave

  • Network Intrusion Detection Systems
  • NIDS

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