Until now, researchers have been analyzing Android applications dynamically with the use of either emulators or real devices. Emulators are an option that testers currently have to achieve scalability. Besides, these approaches can also take snapshots which help to revert back to a known state in a matter of seconds. However, emulators are often slow in performance and contain heuristic emulation traces. As for the case of real devices, restoring mechanism and hardware utilization are limitations for increasing analysis productivity. In this paper, we developed C-Android with the motivation to seek an alternative solution to solve the existing problems. C-Android leverages Linux container technology to provide restore mechanism on the bare-metal device and to utilize the most from existing hardware. To study on the opportunities of applying Android container into the analysis, we have performed several comparative implementations between C-Android and other existing approaches. The purpose of our first comparison is to assess the compatibility between container-based (C-Android) and existing solutions. The following test is related to performance between our approach and other platforms. Lastly, the utilization test is established in order to assess the possibility to optimize C-Android hardware without causing too much reduction in the performance. The challenges of applying container technology to Android analysis are also discussed in the paper as a result of our study.

到目前为止，研究人员一直在使用模拟器或真实设备来动态分析Android应用程序。仿真器是测试人员当前必须实​​现可伸缩性的一种选择。此外，这些方法还可以拍摄快照，这有助于在几秒钟内恢复到已知状态。但是，仿真器的性能通常很慢，并且包含启发式仿真痕迹。对于真实设备，恢复机制和硬件利用率是提高分析效率的限制。在本文中，我们开发C-Android的动机是寻求替代解决方案来解决现有问题。C-Android利用Linux容器技术在裸机设备上提供还原机制，并充分利用现有硬件。为了研究将Android容器应用到分析中的机会，我们在C-Android和其他现有方法之间进行了几种比较实现。我们第一个比较的目的是评估基于容器的（C-Android）与现有解决方案之间的兼容性。以下测试与我们的方法与其他平台之间的性能有关。最后，建立利用率测试，以评估优化C-Android硬件的可能性，而不会导致性能降低过多。作为我们研究的结果，本文还讨论了将容器技术应用于Android分析的挑战。我们第一个比较的目的是评估基于容器的（C-Android）与现有解决方案之间的兼容性。以下测试与我们的方法与其他平台之间的性能有关。最后，建立利用率测试，以评估优化C-Android硬件的可能性，而不会导致性能降低过多。作为我们研究的结果，本文还讨论了将容器技术应用于Android分析的挑战。我们第一个比较的目的是评估基于容器的（C-Android）与现有解决方案之间的兼容性。以下测试与我们的方法与其他平台之间的性能有关。最后，建立利用率测试，以评估优化C-Android硬件的可能性，而不会导致性能降低过多。作为我们研究的结果，本文还讨论了将容器技术应用于Android分析的挑战。