Framework for malware analysis in Android

Authors

DOI:

https://doi.org/10.18046/syt.v14i37.2241

Keywords:

Framework, machine learning, security, Google, malware.

Abstract

Android is a open source operating system with more than a billion of users, including all kind of devices (cell phones, TV, smart watch, etc). The amount of sensitive data “using” this technologies has increased the cyber criminals interest to develop tools and techniques to acquire that information or to disrupt the device's smooth operation. Despite several solutions are able to guarantee an adequate level of security, day by day the hackers skills grows up (because of their growing experience), what means a permanent challenge for security tools developers. As a response, several members of the research community are using artificial intelligence tools for Android security, particularly machine learning techniques to classify between healthy and malicious apps; from an analytic review of those works, this paper propose a static analysis framework and machine learning to do that classification.

Author Biographies

  • Christian Urcuqui-López, Grupo de Investigación i2t, Universidad Icesi Cali,

    Systems Engineer (emphasis in Management and Computing) and Master in Computing Management and Telecommunications from Universidad Icesi (Cali-Colombia). Member of Informatics and Telecommunications research group [i2t]. His areas of interest include: artificial intelligence, machine learning and security applied to informatics. 

     

     

  • Andrés Navarro Cadavid, Grupo de Investigación i2t, Universidad Icesi Cali,
    Electronic Engineer and Magister in Technology Management of the Universidad Pontificia Bolivariana (Medellín, Colombia) and Doctor of Engineering in Telecommunications of the Universidad Politécnica de Valencia (Spain). Full time professor and leader of the Informatics and Telecommunications research group (i2T) attached to the Information and Communications Department at the Universidad Icesi (Cali-Colombia). Counselor at the National Program of Electronics, Telecommunications and Informatics [ETI]. His areas of interest include Spectrum Management, Cognitive Radio, and Telematics solutions for health

Downloads

Published

2016-08-05

Issue

Section

Discussion papers