Securing highly-sensitive information in smart mobile devices through difficult-to-mimic and single-time usage analytics

Saiyma Sarmin, Nafisa Anzum, Kazi Hasan Zubaer, Farzana Rahman, A. B.M.Alim Al Islam

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

Abstract

The ability of smart devices to recognize their owners or valid users gains attention with the advent of widespread highly sensitive usage of these devices such as storing secret and personal information. Unlike the existing techniques, in this paper, we propose a very lightweight single-time user identification technique that can ensure a unique authentication by presenting a system near-to-impossible to breach for intruders. Here, we have conducted a thorough study over single-time usage data collected from 33 users. The study reveals several new findings, which in turn, leads us to a novel solution exploiting a new machine learning technique. Our evaluation confirms that the proposed solution operates with only 5% False Acceptance Rate (FAR) and only 6% False Rejection Rate (FRR) over the data collected from 33 users. We further evaluate the performance through comparing its performance with some existing machine learning techniques. Finally, we perform a real implementation of our proposed solution as a mobile application to conduct a rigorous user evaluation over 27 participants using three different devices in order to show how the solution works in practical situations. Outcomes of the user evaluation demonstrate as low as 0% FAR after letting intruders to mimic the actual user, which ensures extremely low probability of being breached. Moreover, we let 2 users to continuously use our application over 25 days in different states during their operation. Outcomes of this evaluation demonstrate as low as 1% FRR confirming the usability of our technique in long-term usage.

Original languageEnglish (US)
Title of host publicationProceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems
Subtitle of host publicationComputing, Networking and Services, Mobiquitous 2018
PublisherAssociation for Computing Machinery
Pages322-331
Number of pages10
ISBN (Electronic)9781450360937
DOIs
StatePublished - Nov 5 2018
Externally publishedYes
Event15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, Mobiquitous 2018 - New York, United States
Duration: Nov 5 2018Nov 7 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, Mobiquitous 2018
CountryUnited States
CityNew York
Period11/5/1811/7/18

Keywords

  • Behavioral biometrics
  • Mean-SD clustering
  • Security
  • Smartphone

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Sarmin, S., Anzum, N., Zubaer, K. H., Rahman, F., & Al Islam, A. B. M. A. (2018). Securing highly-sensitive information in smart mobile devices through difficult-to-mimic and single-time usage analytics. In Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, Mobiquitous 2018 (pp. 322-331). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3286978.3287012