Abstract
Over the last few years, computers and smartphones have become essential tools in our ways of communicating with each-other. Nowadays, the amount of applications in the Google store has grown exponentially, therefore, malware developers have introduced malicious applications in that market. The Android system uses the Dalvik virtual machine. Through reverse engineering, we may be able to get the different opcodes for each application. For this reason, in this paper an approach to detect malware on Android is presented, by using the techniques of reverse engineering and putting an emphasis on operational codes used for these applications. After obtaining these opcodes, machine learning techniques are used to classify apps.
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Notes
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Weka: Data Mining Software is a collection of machine learning algorithms for automated data mining tasks: http://www.cs.waikato.ac.nz/ml/weka/.
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Adware is a type of action hidden in applications, which send targeted advertisements to our device when you run an application.
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de la Puerta, J.G., Sanz, B., Santos, I., Bringas, P.G. (2015). Using Dalvik Opcodes for Malware Detection on Android. In: Onieva, E., Santos, I., Osaba, E., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2015. Lecture Notes in Computer Science(), vol 9121. Springer, Cham. https://doi.org/10.1007/978-3-319-19644-2_35
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