Dynamic analysis of Android applications to extract spam caller IDs

Bachelor thesis (2022)

Authors

C.C. van Luik Electrical Engineering, Mathematics and Computer Science

Contributors

A. Zarras Cyber Security - EEMCS (mentor)
Y. Zhauniarovich Organisation & Governance - TPM (mentor)
G.J.P.M. Houben Web Information Systems - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Christiaan van Luik
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Published Date

23-06-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Spam calls are becoming an increasing problem, with people receiving multiple spam calls per month on average. Multiple Android applications exist that are able to detect spam calls and display a warning or block such calls. Little is known however on how these applications work and what numbers they block.
In this research, the following question is investigated: Can we do a brute force dynamic analysis on Android spam call blocking apps, to extract caller ID information from apps that cannot be or is not extracted through static analysis? A tool is created that is capable of doing such a dynamic analysis, by installing such an app on an emulator, sending emulated phone calls to the emulator, and using screenshot comparison techniques to determine whether the call is classified as allowed or blocked by the respective app. The tool developed in this research can, fully automated, test caller IDs on 8 different Android apps. Apart from a number of initial setup steps to install and configure the apps in the emulator, the tool takes about 1.5 seconds on average to analyze 1 caller IDs on one app.