Mobile malware detection
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Date
2022-06-10
Journal Title
Journal ISSN
Volume Title
Publisher
UNIVERSITY of M'SILA
Abstract
With the advent of communication technologies and the extended availability of smart
devices (smartphones, PDAs), mobiles applications are becoming part of our everyday life, due
to its portability, availability and high performance services to
cover most user’s needs. Like all web applications, mobile system is exposed to
malware attacks.
In this context, our project is aimed at developing a mobile malware detector (MobMal
detector) on Android platform using machine learning approach to detect malware by mining the
patterns of Permissions and API Calls.
Description
Keywords
Mobile application ‘s malware, Android Permission, API Calls, Malware Apps, Support Vector Machines.