A Website Fingerprinting Attack based on the Virtual Memory of the Process on Android Devices

Website Fingerprinting Attack (WFA) which identifies websites browsed on Android devices is extremely dangerous because it creates an opportunity for stealing private information. As the most feasible WFA method, we focus on a method that can identify a website by using the power consumption model restored from CPU data. However, that is not effective in a real situation where multiple background tasks run because CPU data which are unrelated to browsing are confused. Furthermore, the previous method cannot accurately identify simple websites that are subject to background tasks. Thus, a more feasible method is required to indicate the dangers. In this paper, we propose a website fingerprinting attack based on virtual memory of process on Android device. We focus on the fact that a specific process about browsing websites works when a website is browsed. Because each process has its virtual memory which is independent of each other, the useful feature of a task can be extracted from the virtual memory without noise. Therefore, the proposed method can precisely identify a browsed website by using the virtual memory-based features even if background tasks work. Furthermore, the proposed method can obtain effective information even for a simple website. By computer simulation with a real dataset, we demonstrate that the proposed method can improve up to 86%, 89%, and 82% in precision, recall, and F-measure, respectively for websites which the previous scheme cannot identify at all.