A framework for selecting classification models in the intruder detection system using TOPSIS


Abstract:

As the network has expanded considerably, security mechanisms are a key issue in networks. Intrusive activities, such as unauthorized access and data manipulation, are increasing. Therefore, the role of the Network Intrusion Detection System (NIDS) in monitoring network traffic for activity and determining whether an intrusion has occurred is very important. The performance of an IDS depends on the selection of the classification model and training data, however, many classifiers generate similar results when measuring performance. The technique of order of preference for similarity to the ideal solution (TOPSIS) is used to select one or more alternatives based on the criteria. The main objective is to present some classification models used in a data set to select the best alternative according to the performance criteria using the TOPSIS method. The deductive method and selection research technique were …

Año de publicación:

2021

Keywords:

  • INTRUSION DETECTION SYSTEM (IDS)
  • TOPSIS
  • NSL-KDD
  • Machine Learning

Fuente:

scopusscopus
googlegoogle
orcidorcid

Tipo de documento:

Other

Estado:

Acceso abierto

Áreas de conocimiento:

  • Inteligencia artificial
  • Algoritmo
  • Aprendizaje automático

Áreas temáticas de Dewey:

  • Métodos informáticos especiales
  • Ciencias de la computación
Procesado con IAProcesado con IA

Objetivos de Desarrollo Sostenible:

  • ODS 9: Industria, innovación e infraestructura
  • ODS 16: Paz, justicia e instituciones sólidas
  • ODS 17: Alianzas para lograr los objetivos
  • ODS 8: Trabajo decente y crecimiento económico
Procesado con IAProcesado con IA