Construcción de clasificadores de malware para agencias de seguridad del Estado

  • David Esteban Useche-Peláez Escuela Colombiana de Ingeniería Julio Garavito
  • Daniel Orlando Díaz-López Escuela Colombiana de Ingeniería Julio Garavito
  • Daniela Sepúlveda-Alzate Escuela Colombiana de Ingeniería Julio Garavito
  • Diego Edison Cabuya-Padilla Comando Conjunto Cibernético
Keywords: Cuckoo sandbox, ciencia de datos, aprendizaje de máquina, análisis de malware, sandboxing


El sandboxing ha sido usado de manera regular para analizar muestras de software y determinar si estas contienen propiedades o comportamientos sospechosos. A pesar de que el sandboxing es una técnica poderosa para desarrollar análisis de malware, esta requiere que un analista de malware desarrolle un análisis riguroso de los resultados para determinar la naturaleza de la muestra: goodware o malware. Este artículo propone dos modelos de aprendizaje automáticos capaces de clasificar muestras con base a un análisis de firmas o permisos extraídos por medio de Cuckoo sandbox, Androguard y VirusTotal. En este artículo también se presenta una propuesta de arquitectura de centinela IoT que protege dispositivos IoT, usando uno de los modelos de aprendizaje automáticos desarrollados anteriormente. Finalmente, diferentes enfoques y perspectivas acerca del uso de sandboxing y aprendizaje automático por parte de agencias de seguridad del Estado también son aportados.


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Author Biographies

David Esteban Useche-Peláez, Escuela Colombiana de Ingeniería Julio Garavito

Ingeniero de Sistemas (c). Escuela Colombiana de Ingeniería Julio Garavito. Bogotá, Colombia

Daniel Orlando Díaz-López, Escuela Colombiana de Ingeniería Julio Garavito

Ph.D. en Informática. Escuela Colombiana de Ingeniería Julio Garavito. Bogotá, Colombia

Daniela Sepúlveda-Alzate, Escuela Colombiana de Ingeniería Julio Garavito

Ingeniera de Sistemas (c). Escuela Colombiana de Ingeniería Julio Garavito. Bogotá, Colombia

Diego Edison Cabuya-Padilla, Comando Conjunto Cibernético

M.Sc. en Gestión de la Información. Comando Conjunto Cibernético. Bogotá, Colombia.


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How to Cite
Useche-Peláez, D., Díaz-López, D., Sepúlveda-Alzate, D., & Cabuya-Padilla, D. (2018). Construcción de clasificadores de malware para agencias de seguridad del Estado. ITECKNE, 15(2), 107-121.
Research and Innovation Articles