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dc.contributor.authorAlzaylaee, M.K.en
dc.contributor.authorYerima, Suleimanen
dc.contributor.authorSezer, Sakiren
dc.date.accessioned2018-10-31T10:19:12Z
dc.date.available2018-10-31T10:19:12Z
dc.date.issued2016-06
dc.identifier.citationAlzaylaee, M. K., Yerima, S. Y. and Sezer, S. (2016) Dynalog: an automated dynamic analysis framework for characterizing android applications. In: Proceedings of the 2016 International Conference On Cyber Security And Protection Of Digital Services (Cyber Security), London, UK.en
dc.identifier.urihttp://hdl.handle.net/2086/16927
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractAndroid is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware that are becoming more sophisticated to evade state-of-the-art detection approaches. Many Android malware families employ obfuscation techniques in order to avoid detection and this may defeat static analysis based approaches. Dynamic analysis on the other hand may be used to overcome this limitation. Hence in this paper we propose DynaLog, a dynamic analysis based framework for characterizing Android applications. The framework provides the capability to analyse the behaviour of applications based on an extensive number of dynamic features. It provides an automated platform for mass analysis and characterization of apps that is useful for quickly identifying and isolating malicious applications. The DynaLog framework leverages existing open source tools to extract and log high level behaviours, API calls, and critical events that can be used to explore the characteristics of an application, thus providing an extensible dynamic analysis platform for detecting Android malware. DynaLog is evaluated using real malware samples and clean applications demonstrating its capabilities for effective analysis and detection of malicious applications.en
dc.language.isoenen
dc.publisherIEEEen
dc.subjectandroid application analysisen
dc.subjectandroid malwareen
dc.subjectmobile computingen
dc.subjectmalware detectionen
dc.subjectdynamic analysisen
dc.subjectinvasive softwareen
dc.subjectmalware obfuscationen
dc.titleDynalog: An Automated Dynamic Analysis Framework for Characterizing Android Applicationsen
dc.typeConferenceen
dc.identifier.doihttps://doi.org/10.1109/cybersecpods.2016.7502337
dc.researchgroupCyber Technology Institute (CTI)en
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceCC-BY-NCen
dc.date.acceptance2016en
dc.researchinstituteCyber Technology Institute (CTI)en
dc.exception.ref2021codes254aen


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