SwipeVLock: A Supervised Unlocking Mechanism Based on Swipe Behavior on Smartphones

Wenjuan Li, Jiao Tan, Weizhi Meng*, Yu Wang, Jing Li

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

40 Downloads (Pure)

Abstract

Smartphones have become a necessity in people’s daily lives, and changed the way of communication at any time and place. Nowadays, mobile devices especially smartphones have to store and process a large amount of sensitive information, i.e., from personal to financial and professional data. For this reason, there is an increasing need to protect the devices from unauthorized access. In comparison with the traditional textual password, behavioral authentication can verify current users in a continuous way, which can complement the existing authentication mechanisms. With the advanced capability provided by current smartphones, users can perform various touch actions to interact with their devices. In this work, we focus on swipe behavior and aim to design a machine learning-based unlock scheme called SwipeVLock, which verifies users based on their way of swiping the phone screen with a background image. In the evaluation, we measure several typical supervised learning algorithms and conduct a user study with 30 participants. Our experimental results indicate that participants could perform well with SwipeVLock, i.e., with a success rate of 98% in the best case.

Original languageEnglish
Title of host publicationProceedings of 2nd International Conference on Machine Learning for Cyber Security
EditorsXiaofeng Chen, Xinyi Huang, Jun Zhang
Number of pages14
PublisherSpringer
Publication date1 Jan 2019
Pages140-153
ISBN (Print)9783030306182
DOIs
Publication statusPublished - 1 Jan 2019
Event2nd International Conference on Machine Learning for Cyber Security, ML4CS 2019 - Xi'an, China
Duration: 19 Sep 201921 Sep 2019

Conference

Conference2nd International Conference on Machine Learning for Cyber Security, ML4CS 2019
CountryChina
CityXi'an
Period19/09/201921/09/2019
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11806 LNCS
ISSN0302-9743

Keywords

  • Behavioral biometric
  • Smartphone security
  • Swipe behavior
  • Touch action
  • User authentication

Fingerprint Dive into the research topics of 'SwipeVLock: A Supervised Unlocking Mechanism Based on Swipe Behavior on Smartphones'. Together they form a unique fingerprint.

Cite this