Robust Detection of Android UI Similarity
| Autor: | Yaoqi Jia, Xuxian Jiang, Zhenkai Liang, Hanjun Ma, Jian Mao, Jingdong Bian |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
ComputerSystemsOrganization_COMPUTERSYSTEMIMPLEMENTATION
InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g. HCI) GeneralLiterature_INTRODUCTORYANDSURVEY Computer science InformationSystems_INFORMATIONSYSTEMSAPPLICATIONS 020207 software engineering 02 engineering and technology Phishing GeneralLiterature_MISCELLANEOUS Visualization Information sensitivity Human–computer interaction 020204 information systems mental disorders 0202 electrical engineering electronic engineering information engineering Android (operating system) User interface |
| Zdroj: | ICC |
| DOI: | 10.1109/icc.2018.8422189 |
| Popis: | The similarity of the user interfaces (UIs) among Android apps is an important factor to indicate abnormal behaviors in Android apps. For example, phishing apps use UIs similar to those of their target apps to lure users to input sensitive information. As another example, repackaged apps preserve the UIs of the original apps while adding malicious code. In this paper, we propose a novel solution, GeminiScope, to robustly detect similar UIs among Android apps. Our approach analyzes the UI layouts of Android apps, extracts the fundamental features of the UIs' visual appearance, and rates the similarity among the UIs of apps. We evaluated GeminiScope using a few sets of apps from various sources. It reliably detected apps with similar UIs, showing the potential of using visual similarity as a unique feature to detect malicious apps. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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