An Efficient, Robust, and Scalable Approach for Analyzing Interacting Android Apps

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Tsutano, Yutaka, Bachala, Shakthi, Srisa-An, Witawas, Rothermel, Gregg, Dinh, Jackson
Format: Conference Proceeding
Language:English
Subjects:
Android
Androids
Humanoid robots
inter-app communication
Java
Libraries
program analysis
Robustness
Security
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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 real-world 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-the-art 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.
ISSN:1558-1225
DOI:10.1109/ICSE.2017.37