TMGuard: A touch movement-based security mechanism for screen unlock patterns on smartphones

Weizhi Meng, Wenjuan Li, Duncan S. Wong, Jianying Zhou

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

23 Citations (Scopus)


Secure user authentication is a big challenge for smartphone security. To overcome the drawbacks of knowledge-based method, various graphical passwords have been proposed to enhance user authentication on smartphones. Android unlock patterns are one of the Android OS features aiming to authenticate users based on graphical patterns. However, recent studies have shown that attackers can easily compromise this unlock mechanism (i.e., by means of smudge attacks). We advocate that some additional mechanisms should be added to improve the security of unlock patterns. In this paper, we first show that users would perform a touch movement differently when interacting with the touchscreen and that users would perform somewhat stably for the same pattern after several trials. We then develop a touch movement-based security mechanism, called TMGuard, to enhance the authentication security of Android unlock patterns by verifying users’ touch movement during pattern input. In the evaluation, our user study with 75 participants demonstrate that TMGuard can positively improve the security of Android unlock patterns without compromising its usability.

Original languageEnglish
Title of host publicationApplied Cryptography and Network Security - 14th International Conference, ACNS 2016, Proceedings
EditorsMark Manulis, Steve Schneider, Ahmad-Reza Sadeghi
PublisherSpringer Verlag
Number of pages19
ISBN (Print)9783319395548
Publication statusPublished - 2016
Externally publishedYes
Event14th International Conference on Applied Cryptography and Network Security, ACNS 2016 - Guildford, United Kingdom
Duration: 19 Jun 201622 Jun 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th International Conference on Applied Cryptography and Network Security, ACNS 2016
Country/TerritoryUnited Kingdom


  • Android unlock patterns
  • Behavioral biometric
  • Mobile security
  • Touch gestures
  • Usability
  • User authentication

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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