@Article{2019.100000079,
AUTHOR = {Tianjun Wu, Yuexiang Yang},
TITLE = {Detecting Android Inter-App Data Leakage Via Compositional Concolic Walking},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {25},
YEAR = {2019},
NUMBER = {4},
PAGES = {755--766},
URL = {http://www.techscience.com/iasc/v25n4/39697},
ISSN = {2326-005X},
ABSTRACT = {While many research efforts have been around auditing individual android apps, 
the security issues related to the interaction among multiple apps are less 
studied. Due to the hidden nature of Inter-App communications, few existing 
security tools are able to detect such related vulnerable behaviors. This paper 
proposes to perform overall security auditing using dynamic analysis techniques. 
We focus on data leakage as it is one of the most common vulnerabilities for 
Android applications. We present an app auditing system AppWalker, which uses 
concolic execution on a set of apps. We use static Inter-App taint analysis to 
guide the dynamic auditing procedure, so that we can target at potential InterApp data leakage. To mitigate the exponential blow-up when auditing various 
combinations of apps, we introduce a novel technique called compositional 
concolic walking. In the end of the auditing, the event and data inputs created 
during concolic walking are fed to the app set. By dynamically checking the 
triggered data-leaking behavior, we are then able to confirm the existence of 
Inter-App data leakage. AppWalker takes into account both intra- and inter-app 
communications, and is the first research work on dynamic audit of inter-app 
vulnerabilities in a path-sensitive way to our knowledge. Experimental results 
reveal that our method can effectively detect real-world Inter-App data leakage.},
DOI = {10.31209/2019.100000079}
}