Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/77225
Title: Malware detection application for android using machine learning
Authors: Loh, Jing Kai
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2019
Abstract: Mobile phones especially smartphone is now an essential item in today’s society, granting user’s ability to perform tasks and brining convenience to its user. While IOS popularity is constantly growing, android still commands much of the market share and thus has been seen as a lucrative market for malicious actors to benefit off this huge market. Although a variety of methods exist to protect users from these malicious actors, those solutions tend to have negative drawbacks to them. Thus, new way to be able to detect these malwares is needed. In this project, the focus will be on the development of malware detection tool that will be located on the android platform. It will use the features located in the APK alongside machine learning to predict if an APK is malicious or benign. While certain aspect of the machine learning and deployment to android generated good outcome, several issues were identified during the development and testing.
URI: http://hdl.handle.net/10356/77225
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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