Towards detection of juice filming charging attacks via supervised CPU usage analysis on smartphones

Weizhi Meng, Lijun Jiang, Kim Kwang Raymond Choo, Yu Wang*, Chong Jiang

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Mobile devices, such as Android and iOS devices, are an attractive target for cyber-criminals, due to the amount of private data that can be accessed or stored on such devices. As public charging facilities become more commonplace, phone charging attacks are no longer fiction. Juice filming charging (JFC) attack is a particular phone charging threat, which can capture or infer users’ private information by automatically recording screen information from mobile devices during the entire charging process. In this work, we first investigate the types of phone applications users would interact with the most when charging their devices. Then, we propose a detection approach for JFC attacks solely by analyzing CPU usage. In the evaluation, we collect data from a total of 187 participants, and the findings show that our approach using the SVM classifier can achieve better performance than other approaches. Our work complements existing security mechanisms against charging threats.

Original languageEnglish
JournalComputers & Electrical Engineering
Volume78
Pages (from-to)230-241
ISSN0045-7906
DOIs
Publication statusPublished - 1 Sep 2019

Keywords

  • Android and iOS security
  • Charging threat
  • CPU usage analysis
  • JFC attack
  • Supervised machine learning

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