Continuous authentication using one-class classifiers and their fusion

Rajesh Kumar, Partha Pratim Kundu, Vir Phoha

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

4 Citations (Scopus)

Abstract

While developing continuous authentication systems (CAS), we generally assume that samples from both genuine and impostor classes are readily available. However, the assumption may not be true in certain circumstances. Therefore, we explore the possibility of implementing CAS using only genuine samples. Specifically, we investigate the usefulness of four one-class classifiers OCC (elliptic envelope, isolation forest, local outliers factor, and one-class support vector machines) and their fusion. The performance of these classifiers was evaluated on four distinct behavioral biometric datasets, and compared with eight multi-class classifiers (MCC). The results demonstrate that if we have sufficient training data from the genuine user the OCC, and their fusion can closely match the performance of the majority of MCC. Our findings encourage the research community to use OCC in order to build CAS as it does not require knowledge of impostor class during the enrollment process.

Original languageEnglish (US)
Title of host publication2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis, ISBA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
Volume2018-January
ISBN (Electronic)9781538622483
DOIs
StatePublished - Mar 9 2018
Event4th IEEE International Conference on Identity, Security, and Behavior Analysis, ISBA 2018 - Singapore, Singapore
Duration: Jan 11 2018Jan 12 2018

Other

Other4th IEEE International Conference on Identity, Security, and Behavior Analysis, ISBA 2018
CountrySingapore
CitySingapore
Period1/11/181/12/18

Fingerprint

Authentication
Classifiers
Fusion reactions
Research
local factors
performance
social isolation
Biometrics
Support vector machines
community
Forests
Datasets
Support Vector Machine
biometrics

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Safety, Risk, Reliability and Quality
  • Behavioral Neuroscience
  • Social Sciences (miscellaneous)

Cite this

Kumar, R., Kundu, P. P., & Phoha, V. (2018). Continuous authentication using one-class classifiers and their fusion. In 2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis, ISBA 2018 (Vol. 2018-January, pp. 1-8). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISBA.2018.8311467

Continuous authentication using one-class classifiers and their fusion. / Kumar, Rajesh; Kundu, Partha Pratim; Phoha, Vir.

2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis, ISBA 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-8.

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

Kumar, R, Kundu, PP & Phoha, V 2018, Continuous authentication using one-class classifiers and their fusion. in 2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis, ISBA 2018. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-8, 4th IEEE International Conference on Identity, Security, and Behavior Analysis, ISBA 2018, Singapore, Singapore, 1/11/18. https://doi.org/10.1109/ISBA.2018.8311467
Kumar R, Kundu PP, Phoha V. Continuous authentication using one-class classifiers and their fusion. In 2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis, ISBA 2018. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-8 https://doi.org/10.1109/ISBA.2018.8311467
Kumar, Rajesh ; Kundu, Partha Pratim ; Phoha, Vir. / Continuous authentication using one-class classifiers and their fusion. 2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis, ISBA 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-8
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