Proposing Automatic Dataset Generation System to Support Android Sensitive Data Leakage Detection Systems

HIEN DO
2:04 08/05/2019

Android sensitive information leakage datasets studies are still limited. Specifically, DroidBench dataset contains 120 case studies of which only 3 case studies are used for analyzing inter-application data flow. Therefore, increasing the number of case study of Android sensitive information leakage datasets is necessary to contribute to improving the accuracy of the evaluations of related research studies in the future. Besides this, the creation of datasets for the evaluation of systems for analyzing other components of the Android operating system such as Application Framework, Linux Kernel, ... is also necessary. In this paper, we propose a system that allows creation of test cases to assess sensitive information leakage detection systems on devices which are using Android operating systems. This system allows creating datasets containing case studies that cause sensitive data leakage not only in a chain of applications but also in the Application Framework component. Evaluation results show that the proposed system works stably with case studies which have a large number of application chains up to 1000 applications and 20 inter-application communication channels for each application pair.

TIN LIÊN QUAN
The proliferation of connectivity through modern telecommunications has led to increased unwanted and disruptive calls. Such communications negatively impact user experience and trust in platforms. Currently, call filtering relies on centralized architectures that aggregate vast troves of sensitive user data within single entities, compromising privacy and ownership. Users have limited...