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|Title:||Malware detection for mobile devices||Authors:||Chia, Jia Hong||Keywords:||DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing||Issue Date:||2017||Abstract:||Mobile devices have increasingly become targets for malware due to the lucrative rewards for user's personal information. As such, malware detection and classification tools are valuable and sought after by many agencies. This report aims to discuss an automated system for extracting learning features to detect and classify malware that uses the native library to target the Android operating system. The report will also present a parser to extract the sequence of API calls to depict the behavior of a given application. Through the utilization of a reverse engineering tool and a disassembler, the extracted features can be used to classify malware with the use of Machine Learning Technique||URI:||http://hdl.handle.net/10356/70208||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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