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Detection and Visualization of Android Malware Behavior
Electronics and Computing Department, Mondragon University, Mondragon, Spain; National University of Engineering (UNI), P.O. Box 5595, Managua, Nicaragua .
Electronics and Computing Department, Mondragon University, Mondragon, Spain.
Electronics and Computing Department, Mondragon University, Mondragon, Spain.
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
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2016 (English)In: Journal of Electrical and Computer Engineering, ISSN 2090-0147, Vol. 2016, article id 8034967Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Hindawi Publishing Corporation, 2016. Vol. 2016, article id 8034967
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:liu:diva-134405DOI: 10.1155/2016/8034967OAI: oai:DiVA.org:liu-134405DiVA: diva2:1072971
Available from: 2017-02-09 Created: 2017-02-09 Last updated: 2018-01-13

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CiteExportLink to record
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