Virtual Safe: Unauthorized movement detection for mobile devices

Dakun Shen, Ian Markwood, Dan Shen, Yao Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The prevalence and monetary value of mobile devices, coupled with their compact and, indeed, mobile nature, lead to frequent theft due to a lack of proper anti-theft mechanisms. Currently there only exist damage control efforts such as remote wiping the device's memory or GPS tracking, but nothing to notify users of theft while it takes place. We propose such a mechanism which utilizes the unique motion patterns inherent to humans and differentiate our work from other motion behavior studies by using it as first-order authentication and developing matching methods fast enough to act as an actual anti-theft system. We test our system with the aid of 45 volunteers and demonstrate detection of unauthorized movement within 10 to 20 steps with an accuracy of 96.4% to 97.5%, while simultaneously distinguishing owners as themselves with 97.8% accuracy.

Original languageEnglish
Title of host publication2016 IEEE Conference on Communications and Network Security, CNS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages315-323
Number of pages9
ISBN (Electronic)9781509030651
DOIs
StatePublished - Feb 21 2017
Event2016 IEEE Conference on Communications and Network Security, CNS 2016 - Philadelphia, United States
Duration: Oct 17 2016Oct 19 2016

Publication series

Name2016 IEEE Conference on Communications and Network Security, CNS 2016

Conference

Conference2016 IEEE Conference on Communications and Network Security, CNS 2016
Country/TerritoryUnited States
CityPhiladelphia
Period10/17/1610/19/16

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