Memorias de investigación
Communications at congresses:
Increasing Detection Rate of User-to-Root Attacks Using Genetic Algorithms
Year:2007

Research Areas
  • Processing and signal analysis

Information
Abstract
In this work we have presented a genetic algorithm approach for implementing rules deployed to detect various types of attacks. We have used the features identified as the most important ones for each attack type to form the rules in order to get a high detection rate. These features were identified by deploying principal component analysis and multi expression programming. Thenceforth we have used serial combination of the rules implemented for detection of user-to-root attacks with the rules implemented for detection of other types of attacks in order to decrease the false-positive rate. The model was verified on KDD99 intrusion detection dataset, demonstrating higher detection rates than those reported by the stateof-the-art, while using small subset of features from the original set.
International
Si
Congress
International Conference on Emerging Security Information, Systems and Technologies, Securware'07
960
Place
Valencia (España)
Reviewers
Si
ISBN/ISSN
0-7695-2989-5
Start Date
14/10/2007
End Date
20/10/2007
From page
To page
Participants

Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Laboratorio de Sistemas Integrados (LSI)
  • Departamento: Ingeniería Electrónica