Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/68976
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dc.contributor.authorLiu, Jinliang-
dc.date.accessioned2016-08-22T02:11:04Z-
dc.date.available2016-08-22T02:11:04Z-
dc.date.issued2016-
dc.identifier.urihttp://hdl.handle.net/10356/68976-
dc.description.abstractWith the arising of smartphone usage, especially for Android OS, users are relying on their mobile devices increasingly. However, Android Malware brings significant threats to the eco-system. In this project, several effective Malware detection tools are implemented and afterwards evaluated on their accuracy and efficiency. Also, several commonly used classifiers are implemented and their performances are compared in classifying Android Malware. Additionally, concept drift in Android Malware is studied and evaluated on certain Malware datasets.en_US
dc.format.extent84 p.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processingen_US
dc.titlePopular tools for malware data analysisen_US
dc.typeThesis
dc.contributor.supervisorChen Lihuien_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Signal Processing)en_US
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