Please use this identifier to cite or link to this item:
Title: Popular tools for malware data analysis
Authors: Liu, Jinliang
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2016
Abstract: With 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.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

Files in This Item:
File Description SizeFormat 
  Restricted Access
3.5 MBAdobe PDFView/Open

Page view(s)

Updated on Jun 18, 2021


Updated on Jun 18, 2021

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.