Network Traffic Analysis for Android Malware Detection

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Abstract

The possibilities offered by the management of huge quantities of equipment and/or networks is attracting a growing number of developers of malware. In this paper, we propose a working methodology for the detection of malicious traffic, based on the analysis of the flow of packets circulating on the network. This objective is achieved through the parameterization of the characteristics of these packages to be analyzed later with supervised learning techniques focused on traffic labeling, so as to enable a proactive response to the large volume of information handled by current filters.

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de la Puerta, J. G., Pastor-López, I., Sanz, B., & Bringas, P. G. (2019). Network Traffic Analysis for Android Malware Detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11734 LNAI, pp. 468–479). Springer Verlag. https://doi.org/10.1007/978-3-030-29859-3_40

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