Apoyo al SGSI por Medio de la Clasificación de Malware Empleando Análisis de Patrones

Mauricio Macias, Cristian Barria, Alejandra Acuna, Claudio Cubillos

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Nowadays, there are significant amounts of malware codes that are created every day. However, the majority of these samples (malware) are variations of other malware that have been already identified. Therefore, most of the analyzed malware have similar structure among them. In this investigation, we will present a technic to extract features throughout different abstraction levels in order to classify malware codes. This analysis is based on three factors: the position where the malware is detected, the functions' calls from each Dynamic Link Libraries (DLL) and the ten most frequently visited hexadecimals per each malware sample. Once those characteristics are obtained, a descriptive vector of each malware is built. This vector works as a training to different learning machines types (SVM, IBL, and Decision Tree) and as a classification of the variations of malware codes (Virus, Backdoor, Trojan, and Adware). The result in the precision of the classification was 78.38% average where 3 types of learning machines were combined. The classified type as virus and algorithm IB1 (Instance Based Learning, IBL) were considered more accurate. These results are a fundamental support to the management system in information security by combining traditional and new classification and detention techniques of malware codes.

Título traducido de la contribuciónSGSI support throught malware's classification using a pattern analysis
Idioma originalEspañol
Título de la publicación alojada2016 IEEE International Conference on Automatica, ICA-ACCA 2016
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781509011476
DOI
EstadoPublicada - 8 dic 2016
Publicado de forma externa
Evento2016 IEEE International Conference on Automatica, ICA-ACCA 2016 - Curico, Chile
Duración: 19 oct 201621 oct 2016

Serie de la publicación

Nombre2016 IEEE International Conference on Automatica, ICA-ACCA 2016

Conferencia

Conferencia2016 IEEE International Conference on Automatica, ICA-ACCA 2016
País/TerritorioChile
CiudadCurico
Período19/10/1621/10/16

Palabras clave

  • Classification
  • DLL
  • Hexadecimals
  • Learning Machines
  • Malware
  • Position
  • Precision
  • SGSI

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