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

Tatsuya Okazaki, Hiroya Kato, Shuichiro Haruta, Iwao Sasase

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceeding - 2021 26th IEEE Asia-Pacific Conference on Communications, APCC 2021
EditorsMohd Fais Mansor, Nordin Ramli, Mahamod Ismail
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7-12
Number of pages6
ISBN (Electronic)9781728172545
DOIs
Publication statusPublished - 2021
Event26th IEEE Asia-Pacific Conference on Communications, APCC 2021 - Virtual, Kuala Lumpur, Malaysia
Duration: 2021 Oct 112021 Oct 13

Publication series

NameProceeding - 2021 26th IEEE Asia-Pacific Conference on Communications, APCC 2021

Conference

Conference26th IEEE Asia-Pacific Conference on Communications, APCC 2021
Country/TerritoryMalaysia
CityVirtual, Kuala Lumpur
Period21/10/1121/10/13

Keywords

  • Android
  • Machine Learning
  • Website Fingerprinting

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Information Systems and Management

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