Automated dynamic detection of self-hiding behavior

dc.contributor.authorBaird, Luke
dc.contributor.authorShan, Zhiyong
dc.contributor.authorNamboodiri, Vinod
dc.date.accessioned2020-05-16T22:46:47Z
dc.date.available2020-05-16T22:46:47Z
dc.date.issued2019-11
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractCertain Android applications, such as but not limited to malware, conceal their presence from the user, exhibiting a self-hiding behavior. Consequently, these apps put the user's security and privacy at risk by performing tasks without the user's awareness. Static analysis has been used to analyze apps for self-hiding behavior, but this approach is prone to false positives and suffers from code obfuscation. This research proposes a set of three tools utilizing a dynamic analysis method of detecting self-hiding behavior of an app in the home, installed, and running application lists on an Android emulator. Our approach proves both highly accurate and efficient, providing tools usable by the Android marketplace for enhanced security screening.en_US
dc.identifier.citationL. Baird, Z. Shan and V. Namboodiri, "Automated Dynamic Detection of Self-Hiding Behavior," 2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems Workshops (MASSW), Monterey, CA, USA, 2019, pp. 87-91en_US
dc.identifier.urihttps://doi.org/10.1109/MASSW.2019.00024
dc.identifier.urihttps://soar.wichita.edu/handle/10057/17654
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.ispartofseriesIEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems Workshops (MASSW);2019
dc.rights.holder© 2019, IEEEen_US
dc.subjectToolsen_US
dc.subjectNavigationen_US
dc.subjectSmart phonesen_US
dc.subjectMalwareen_US
dc.subjectAndroidsen_US
dc.subjectHumanoid robotsen_US
dc.subjectTestingen_US
dc.titleAutomated dynamic detection of self-hiding behavioren_US
dc.typeConference paperen_US
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