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Recent studies observe that app foreground is the most striking componentthat influences the access control decisions in mobile platform, as users tendto deny permission requests lacking visible evidence. However, none of theexisting permission models provides a systematic approach that canautomatically answer the question: Is the resource access indicated by appforeground? In this work, we present the design, implementation, and evaluationof COSMOS, a context-aware mediation system that bridges the semantic gapbetween foreground interaction and background access, in order to protectsystem integrity and user privacy. Specifically, COSMOS learns from a large setof apps with similar functionalities and user interfaces to construct genericmodels that detect the outliers at runtime. It can be further customized tosatisfy specific user privacy preference by continuously evolving with userdecisions. Experiments show that COSMOS achieves both high precision and highrecall in detecting malicious requests. We also demonstrate the effectivenessof COSMOS in capturing specific user preferences using the decisions collectedfrom 24 users and illustrate that COSMOS can be easily deployed on smartphonesas a real-time guard with a very low performance overhead.

Keeping Context In Mind: Automating Mobile App Access Control with User Interface Inspection