A Light-Weight Framework for Pre-submission Vetting of Android Applications in App Stores

  • Boya Li
  • Guojun WangEmail author
  • Haroon Elahi
  • Guihua Duan
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1123)


In general, smartphone apps are rolled-out under a data over-collection based business model. Under this model, users can download and use the apps free of cost, but a large number of permissions are asked from users to access data and resources on their smartphones. Apps collect user data and sell them to interested third-parties for making profits, or abuse smartphone resources for financial gains. This phenomenon introduces privacy and trust issues. Existing vetting mechanisms in the app stores mainly depend on user feedback and expert reviews and only target malicious apps. Permission abusive apps are not included in this list yet. In this paper, we propose a light-weight framework for pre-submission vetting of Android apps by app stores. We generate functional signatures of an app from its description and analyze them to build a profile that contains different permission usage scores, or suggests whether an app is suspicious. This framework can be used in the first line of defense in app stores to vet newly submitted apps.


Android permissions App vetting Privacy Trust 



This work was supported in part by the National Natural Science Foundation of China under Grant 61632009, in part by the Guangdong Provincial Natural Science Foundation under Grant 2017A030308006, and in part by the High-Level Talents Program of Higher Education in Guangdong Province under Grant 2016ZJ01.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Computer ScienceGuangzhou UniversityGuangzhouChina
  2. 2.School of Computer Science and EngineeringCentral South UniversityChangshaChina

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