(2017) Detecting behavior anomalies in graphical user interfaces.
In: Software Engineering Companion (ICSE-C), 2017 IEEE/ACM 39th International Conference on.
Conference:
ICSE International Conference on Software Engineering
Abstract
When interacting with user interfaces, do users always get what they expect? For each user interface element in thousands of Android apps, we extracted the Android APIs they invoke as well as the text shown on their screen. This association allows us to detect outliers: User interface elements whose text, context or icon suggests one action, but which actually are tied to other actions. In our evaluation of tens of thousands of UI elements, our BACKSTAGE prototype discovered misleading random UI elements with an accuracy of 73%.
Item Type: | Conference or Workshop Item (A Paper) (Poster) |
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Conference: | ICSE International Conference on Software Engineering |
Depositing User: | Andreas Rau |
Date Deposited: | 14 Feb 2018 13:43 |
Last Modified: | 18 Jul 2019 12:11 |
Primary Research Area: | NRA4: Secure Mobile and Autonomous Systems |
URI: | https://publications.cispa.saarland/id/eprint/1446 |
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