Doctor of Philosophy (Ph.D.)
Degree Granting Department
Computer Science and Engineering
Xinming Ou, Ph.D.
Jarred Ligatti, Ph.D.
Yao Liu, Ph.D.
Nasir Ghani, Ph.D.
Android App Security Analysis, Mobile Security, Static Analysis
This dissertation presents a new approach to static analysis for security vetting of Android apps, and a general framework called Argus-SAF. Argus-SAF determines points-to information for all objects in an Android app component in a flow and context-sensitive (user-configurable) way and performs data-flow and data dependence analysis for the component. Argus-SAF also tracks inter-component communication activities. It can stitch the component-level information into the app- level information to perform intra-app or inter-app analysis. Moreover, Argus-SAF is NDK/JNI- aware and can efficiently track precise data-flow across language boundary. This dissertation shows that, (a) the aforementioned type of comprehensive app analysis is utterly feasible in terms of computing resources with modern hardware, (b) one can easily leverage the results from this general analysis to build various types of specialized security analyses – in many cases the amount of additional coding needed is around 100 lines of code, and (c) the result of those specialized analyses leveraging Argus-SAF is at least on par and often exceeds prior works designed for the specific problems, which this dissertation demonstrate by comparing Argus-SAF’s results with those of prior works whenever the tool can be obtained. Since Argus-SAF’s analysis directly handles intercomponent and inter-language control and data flows, it can be used to address security problems that result from interactions among multiple components from either the same or different apps and among java code and native code. Argus-SAF’s analysis is sound in that it can assure the absence of the specified security problems in an app with well-specified and reasonable assumptions on Android runtime system and its library.
Scholar Commons Citation
Wei, Fengguo, "Precise, General, and Efficient Data-flow Analysis for Security Vetting of Android Apps" (2018). USF Tampa Graduate Theses and Dissertations.