Protecting private data on mobile systems based on spatio-temporal analysis

Sausan Yazji*, Robert P. Dick, Peter Scheuermann, Goce Trajcevski

*Corresponding author for this work

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

4 Scopus citations

Abstract

Mobile devices such as smart phones and laptops are in common use and carry a vast amount of personal data. This paper presents an efficient behavior-based system for rapidly detecting the Theft of mobile devices in order to protect the private data of their users. Our technique uses spatio-temporal information to construct models of user motion patters. These models are used to detect theft, which may produce anomalous spatio-temporal patterns. We consider two types of user models, each of which builds on the relationship between location ; and time of day. Our evaluation, based on the Reality Mining dataset. shows that our system is capable of detecting an attack within 15 minutes with 81% accuracy.

Original languageEnglish (US)
Title of host publicationPECCS 2011 - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems
Pages114-123
Number of pages10
StatePublished - 2011
Event1st International Conference on Pervasive and Embedded Computing and Communication Systems, PECCS 2011 - Vilamoura, Algarve, Portugal
Duration: Mar 5 2011Mar 7 2011

Publication series

NamePECCS 2011 - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems

Other

Other1st International Conference on Pervasive and Embedded Computing and Communication Systems, PECCS 2011
Country/TerritoryPortugal
CityVilamoura, Algarve
Period3/5/113/7/11

Keywords

  • Mobile security
  • Trajectory analysis

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Communication

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