Visual analytics and visualization for android security risk

Sangbong Yoo, Hong Ryeol Ryu, Hanbyul Yeon, Taekyoung Kwon, Yun Jang

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Nowadays, smart devices enable most of the personal tasks such as banking, mailing, and paperwork that people do on their personal computers (PCs). For this reason, personal information on smart devices has become a good target for malware. Especially, Malware targeted at personal information stored on mobile are hard to detect and risks from usage patterns are even more difficult. The security risk tends to be underestimated by device users and causes critical problems especially on personal information leakage and costing money unconsciously. Malware is also often activated unsuspectedly. Therefore, a means for easy recognition of the problems and the smartphone usage is necessary. In this paper, we present a visual analytics system (VA) for Android security risk lifelog using app permissions to recognize the risk. Our system stores the security-related personal information on the smartphone device and utilizes it to analyze the security risk lifelog. For the risk analysis, we define security risk scores based on the app and permission statistics. Then, several linked visualizations are designed to present the risk lifelog. We have collected the security lifelog data from eight Android smartphone users and analyzed their security matters. Our PVA system enables Android smartphone users to observe, mitigate the security risk, and eventually understand how Android security risk affects their lives. Moreover, we present a user study to evaluate the PVA system with user feedback.

Original languageEnglish
Pages (from-to)9-21
Number of pages13
JournalJournal of Computer Languages
Publication statusPublished - 2019 Aug

Bibliographical note

Funding Information:
This work was supported by the Institute for Information & communications Technology Promotion ( IITP ) grant (no. 2017-0-00380 , Development of next generation user authentication) and (IITP-2019-2016-0-00312, Information Technology Research Center) funded by the Korea government (MSIT).

Publisher Copyright:
© 2019 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Networks and Communications


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