Visible to the public An Efficient, Robust, and Scalable Approach for Analyzing Interacting Android AppsConflict Detection Enabled

TitleAn Efficient, Robust, and Scalable Approach for Analyzing Interacting Android Apps
Publication TypeConference Paper
Year of Publication2017
AuthorsYutaka Tsutano, Shakthi Bachala, Witawas Srisa-an, Gregg Rothermel, Jackson Dinh
Conference Name39th International Conference on Software Engineering
Date Published05/2017
Conference LocationBuenos Aires, Argentina
KeywordsAugust'17, CMU, Race Vulnerability Study and Hybrid Race Detection

When multiple apps on an Android platform interact, faults and security vulnerabilities can occur. Software engineers need to be able to analyze interacting apps to detect such problems. Current approaches for performing such analyses, however, do not scale to the numbers of apps that may need to be considered, and thus, are impractical for application to realworld scenarios. In this paper, we introduce JITANA, a program analysis framework designed to analyze multiple Android apps simultaneously. By using a classloader-based approach instead of a compiler-based approach such as SOOT, JITANA is able to simultaneously analyze large numbers of interacting apps, perform on-demand analysis of large libraries, and effectively analyze dynamically generated code. Empirical studies of JITANA show that it is substantially more efficient than a state-of-theart approach, and that it can effectively and efficiently analyze complex apps including Facebook, Pokemon Go, and Pandora ' that the state-of-the-art approach cannot handle.

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