App behavioral analysis using system calls

dc.contributor.authorDas, Prajit Kumar
dc.contributor.authorJoshi, Anupam
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-10-17T16:34:48Z
dc.date.available2018-10-17T16:34:48Z
dc.date.issued2017-05-01
dc.description2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
dc.description.abstractSystem calls provide an interface to the services made available by an operating system. As a result, any functionality provided by a software application eventually reduces to a set of fixed system calls. Since system calls have been used in literature, to analyze program behavior we made an assumption that analyzing the patterns in calls made by a mobile application would provide us insight into its behavior. In this paper, we present our preliminary study conducted with 534 mobile applications and the system calls made by them. Due to a rising trend of mobile applications providing multiple functionalities, our study concluded, mapping system calls to functional behavior of a mobile application was not straightforward. We use Weka tool with manually annotated application behavior classes and system call features in our experiments, to show that using such features achieves mediocre F1-measure at best. Thus leading to the conclusion that system calls were not sufficient features for mobile application behavior classification.en
dc.description.urihttps://ieeexplore.ieee.org/document/8116425en
dc.format.extent6 pagesen
dc.genreconference paper pre-printen
dc.identifierdoi:10.13016/M2BC3T17F
dc.identifier.citationMayank Jaiswal, Yasir Malik, Fehmi Jaafar, "Android gaming malware detection using system call analysis", Digital Forensic and Security (ISDFS) 2018 6th International Symposium on, pp. 1-5, 2018. DOI: 10.1109/INFCOMW.2017.8116425en
dc.identifier.uri10.1109/INFCOMW.2017.8116425
dc.identifier.urihttp://hdl.handle.net/11603/11576
dc.language.isoenen
dc.publisherIEEEen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rights© 2017 IEEE
dc.subjectGoogleen
dc.subjectMobile handsetsen
dc.subjectAndroidsen
dc.subjectHumanoid robotsen
dc.subjectMobile communicationen
dc.subjectMobile applicationsen
dc.subjectUMBC Ebiquity Research Groupen
dc.titleApp behavioral analysis using system callsen
dc.typeTexten

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