UI Obfuscation and Its Effects on Automated UI Analysis for Android Apps

Hao Zhou, Ting Chen, Haoyu Wang, Le Yu, Xiapu Luo, Ting Wang, Wei Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The UI driven nature of Android apps has motivated the development of automated UI analysis for various purposes, such as app analysis, malicious app detection, and app testing. Although existing automated UI analysis methods have demonstrated their capability in dissecting apps' UI, little is known about their effectiveness in the face of app protection techniques, which have been adopted by more and more apps. In this paper, we take a first step to systematically investigate UI obfuscation for Android apps and its effects on automated UI analysis. In particular, we point out the weaknesses in existing automated UI analysis methods and design 9 UI obfuscation approaches. We implement these approaches in a new tool named UI obfuscator after tackling several technical challenges. Moreover, we feed 3 kinds of tools that rely on automated UI analysis with the apps protected by UI obfuscator, and find that their performances severely drop. This work reveals limitations of automated UI analysis and sheds light on app protection techniques.

Original languageEnglish (US)
Title of host publicationProceedings - 2020 35th IEEE/ACM International Conference on Automated Software Engineering, ASE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages199-210
Number of pages12
ISBN (Electronic)9781450367684
DOIs
StatePublished - Sep 2020
Event35th IEEE/ACM International Conference on Automated Software Engineering, ASE 2020 - Virtual, Melbourne, Australia
Duration: Sep 22 2020Sep 25 2020

Publication series

NameProceedings - 2020 35th IEEE/ACM International Conference on Automated Software Engineering, ASE 2020

Conference

Conference35th IEEE/ACM International Conference on Automated Software Engineering, ASE 2020
CountryAustralia
CityVirtual, Melbourne
Period9/22/209/25/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Safety, Risk, Reliability and Quality

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