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Journal of Electrical and Computer Engineering
Volume 2016, Article ID 8034967, 17 pages
http://dx.doi.org/10.1155/2016/8034967
Research Article

Detection and Visualization of Android Malware Behavior

1Electronics and Computing Department, Mondragon University, 20500 Mondragon, Spain
2National University of Engineering (UNI), P.O. Box 5595, Managua, Nicaragua
3ExoClick SL, 08005 Barcelona, Spain
4Department of Computer and Information Science, Linköping University, 581 83 Linköping, Sweden

Received 7 November 2015; Accepted 7 February 2016

Academic Editor: Aniket Mahanti

Copyright © 2016 Oscar Somarriba et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Malware analysts still need to manually inspect malware samples that are considered suspicious by heuristic rules. They dissect software pieces and look for malware evidence in the code. The increasing number of malicious applications targeting Android devices raises the demand for analyzing them to find where the malcode is triggered when user interacts with them. In this paper a framework to monitor and visualize Android applications’ anomalous function calls is described. Our approach includes platform-independent application instrumentation, introducing hooks in order to trace restricted API functions used at runtime of the application. These function calls are collected at a central server where the application behavior filtering and a visualization take place. This can help Android malware analysts in visually inspecting what the application under study does, easily identifying such malicious functions.