Implicit authentication for smartphone security

Wei Han Lee, Ruby B. Lee

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

5 Scopus citations

Abstract

Common authentication methods based on passwords, or fingerprints in smartphones, depend on user participation. They do not protect against the threat of an attacker getting hold of the phone after the user has been authenticated. Using a victim’s smartphone, the attacker can launch impersonation attacks, which threaten the data that can be accessed from the smartphone and also the security of other users in the network. In this paper, we propose an implicit authentication method using the sensors already built into smartphones. We utilize machine learning algorithms for smartphones to continuously and implicitly authenticate the current user.We compare two typical machine learning methods, SVM and KRR, for authenticating the user. We show that our method achieves high performance (more than 90% authentication accuracy) and high efficiency. Our method needs less than 10 s to train the model and 20 s to detect an abnormal user. We also show that the combination of more sensors provides better accuracy. Furthermore, our method enables adjusting the security level by changing the sampling rate.

Original languageEnglish (US)
Title of host publication1st International Conference on Information Systems Security and Privacy, ICISSP 2015
EditorsOlivier Camp, Esma Aïmeur, Edgar Weippl, Christophe Bidan
PublisherSpringer Verlag
Pages160-176
Number of pages17
ISBN (Print)9783319276670
DOIs
StatePublished - Jan 1 2015
Event1st International Conference on Information Systems Security and Privacy, ICISSP 2015 - Angers, Loire Valley, France
Duration: Feb 9 2015Feb 11 2015

Publication series

NameCommunications in Computer and Information Science
Volume576
ISSN (Print)1865-0929

Other

Other1st International Conference on Information Systems Security and Privacy, ICISSP 2015
CountryFrance
CityAngers, Loire Valley
Period2/9/152/11/15

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

Keywords

  • Accelerometer
  • Android
  • Authentication
  • Magnetometer
  • Orientation sensor
  • Security
  • Sensors
  • Smartphone
  • Support vector machine (SVM)

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  • Cite this

    Lee, W. H., & Lee, R. B. (2015). Implicit authentication for smartphone security. In O. Camp, E. Aïmeur, E. Weippl, & C. Bidan (Eds.), 1st International Conference on Information Systems Security and Privacy, ICISSP 2015 (pp. 160-176). (Communications in Computer and Information Science; Vol. 576). Springer Verlag. https://doi.org/10.1007/978-3-319-27668-7_10