Malware detection techniques for mobile devices

TL;DR

This paper analyzes various malware detection techniques for mobile devices, focusing on Android and iOS, and aims to establish a foundation for developing user-profile-based detection tools.

Contribution

It provides a comparative analysis of existing malware detection methods for Android and iOS, highlighting their advantages and disadvantages, to guide future development.

Findings

Different detection techniques have varying effectiveness and limitations.

Android and iOS require tailored malware detection approaches.

A foundation for user profiling-based malware detection is proposed.

Abstract

Mobile devices have become very popular nowadays, due to its portability and high performance, a mobile device became a must device for persons using information and communication technologies. In addition to hardware rapid evolution, mobile applications are also increasing in their complexity and performance to cover most needs of their users. Both software and hardware design focused on increasing performance and the working hours of a mobile device. Different mobile operating systems are being used today with different platforms and different market shares. Like all information systems, mobile systems are prone to malware attacks. Due to the personality feature of mobile devices, malware detection is very important and is a must tool in each device to protect private data and mitigate attacks. In this paper, analysis of different malware detection techniques used for mobile operating systems is provides. The focus of the analysis will be on the to two competing mobile operating systems - Android and iOS. Finally, an assessment of each technique and a summary of its advantages and disadvantages is provided. The aim of the work is to establish a basis for developing a mobile malware detection tool based on user profiling.