Enhanced free-text keystroke continuous authentication based on dynamics of wrist motion

Borui Li, Han Sun, Yang Gao, Vir Phoha, Zhanpeng Jin

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

4 Citations (Scopus)

Abstract

Free-text keystroke is a form of behavioral biometrics which has great potential for addressing the security limitations of conventional one-time authentication by continuously monitoring the user's typing behaviors. This paper presents a new, enhanced continuous authentication approach by incorporating the dynamics of both keystrokes and wrist motions. Based upon two sets of features (free-text keystroke latency features and statistical wrist motion patterns extracted from the wrist-worn smartwatches), two one-vs-all Random Forest Ensemble Classifiers (RFECs) are constructed and trained respectively. A Dynamic Trust Model (DTM) is then developed to fuse the two classifiers' decisions and realize non-time-blocked real-time authentication. In the free-text typing experiments involving 25 human subjects, an imposter/intruder can be detected within no more than one sentence (average 56 keystrokes) with an FRR of 1.82% and an FAR of 1.94%. Compared with the scheme relying on only keystroke latency which has an FRR of 4.66%, an FAR of 17.92% and the required number of keystroke of 162, the proposed authentication system shows significant improvements in terms of accuracy, efficiency, and usability.

Original languageEnglish (US)
Title of host publication2017 IEEE Workshop on Information Forensics and Security, WIFS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
Volume2018-January
ISBN (Electronic)9781509067695
DOIs
StatePublished - Jan 23 2018
Event2017 IEEE Workshop on Information Forensics and Security, WIFS 2017 - Rennes, France
Duration: Dec 4 2017Dec 7 2017

Other

Other2017 IEEE Workshop on Information Forensics and Security, WIFS 2017
CountryFrance
CityRennes
Period12/4/1712/7/17

Fingerprint

Authentication
Classifiers
Electric fuses
Biometrics
Dynamic models
Monitoring
Experiments
Classifier
Latency

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

Cite this

Li, B., Sun, H., Gao, Y., Phoha, V., & Jin, Z. (2018). Enhanced free-text keystroke continuous authentication based on dynamics of wrist motion. In 2017 IEEE Workshop on Information Forensics and Security, WIFS 2017 (Vol. 2018-January, pp. 1-6). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WIFS.2017.8267642

Enhanced free-text keystroke continuous authentication based on dynamics of wrist motion. / Li, Borui; Sun, Han; Gao, Yang; Phoha, Vir; Jin, Zhanpeng.

2017 IEEE Workshop on Information Forensics and Security, WIFS 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-6.

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

Li, B, Sun, H, Gao, Y, Phoha, V & Jin, Z 2018, Enhanced free-text keystroke continuous authentication based on dynamics of wrist motion. in 2017 IEEE Workshop on Information Forensics and Security, WIFS 2017. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 2017 IEEE Workshop on Information Forensics and Security, WIFS 2017, Rennes, France, 12/4/17. https://doi.org/10.1109/WIFS.2017.8267642
Li B, Sun H, Gao Y, Phoha V, Jin Z. Enhanced free-text keystroke continuous authentication based on dynamics of wrist motion. In 2017 IEEE Workshop on Information Forensics and Security, WIFS 2017. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-6 https://doi.org/10.1109/WIFS.2017.8267642
Li, Borui ; Sun, Han ; Gao, Yang ; Phoha, Vir ; Jin, Zhanpeng. / Enhanced free-text keystroke continuous authentication based on dynamics of wrist motion. 2017 IEEE Workshop on Information Forensics and Security, WIFS 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-6
@inproceedings{0ab67558099c45b7a480cf88addd566b,
title = "Enhanced free-text keystroke continuous authentication based on dynamics of wrist motion",
abstract = "Free-text keystroke is a form of behavioral biometrics which has great potential for addressing the security limitations of conventional one-time authentication by continuously monitoring the user's typing behaviors. This paper presents a new, enhanced continuous authentication approach by incorporating the dynamics of both keystrokes and wrist motions. Based upon two sets of features (free-text keystroke latency features and statistical wrist motion patterns extracted from the wrist-worn smartwatches), two one-vs-all Random Forest Ensemble Classifiers (RFECs) are constructed and trained respectively. A Dynamic Trust Model (DTM) is then developed to fuse the two classifiers' decisions and realize non-time-blocked real-time authentication. In the free-text typing experiments involving 25 human subjects, an imposter/intruder can be detected within no more than one sentence (average 56 keystrokes) with an FRR of 1.82{\%} and an FAR of 1.94{\%}. Compared with the scheme relying on only keystroke latency which has an FRR of 4.66{\%}, an FAR of 17.92{\%} and the required number of keystroke of 162, the proposed authentication system shows significant improvements in terms of accuracy, efficiency, and usability.",
author = "Borui Li and Han Sun and Yang Gao and Vir Phoha and Zhanpeng Jin",
year = "2018",
month = "1",
day = "23",
doi = "10.1109/WIFS.2017.8267642",
language = "English (US)",
volume = "2018-January",
pages = "1--6",
booktitle = "2017 IEEE Workshop on Information Forensics and Security, WIFS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Enhanced free-text keystroke continuous authentication based on dynamics of wrist motion

AU - Li, Borui

AU - Sun, Han

AU - Gao, Yang

AU - Phoha, Vir

AU - Jin, Zhanpeng

PY - 2018/1/23

Y1 - 2018/1/23

N2 - Free-text keystroke is a form of behavioral biometrics which has great potential for addressing the security limitations of conventional one-time authentication by continuously monitoring the user's typing behaviors. This paper presents a new, enhanced continuous authentication approach by incorporating the dynamics of both keystrokes and wrist motions. Based upon two sets of features (free-text keystroke latency features and statistical wrist motion patterns extracted from the wrist-worn smartwatches), two one-vs-all Random Forest Ensemble Classifiers (RFECs) are constructed and trained respectively. A Dynamic Trust Model (DTM) is then developed to fuse the two classifiers' decisions and realize non-time-blocked real-time authentication. In the free-text typing experiments involving 25 human subjects, an imposter/intruder can be detected within no more than one sentence (average 56 keystrokes) with an FRR of 1.82% and an FAR of 1.94%. Compared with the scheme relying on only keystroke latency which has an FRR of 4.66%, an FAR of 17.92% and the required number of keystroke of 162, the proposed authentication system shows significant improvements in terms of accuracy, efficiency, and usability.

AB - Free-text keystroke is a form of behavioral biometrics which has great potential for addressing the security limitations of conventional one-time authentication by continuously monitoring the user's typing behaviors. This paper presents a new, enhanced continuous authentication approach by incorporating the dynamics of both keystrokes and wrist motions. Based upon two sets of features (free-text keystroke latency features and statistical wrist motion patterns extracted from the wrist-worn smartwatches), two one-vs-all Random Forest Ensemble Classifiers (RFECs) are constructed and trained respectively. A Dynamic Trust Model (DTM) is then developed to fuse the two classifiers' decisions and realize non-time-blocked real-time authentication. In the free-text typing experiments involving 25 human subjects, an imposter/intruder can be detected within no more than one sentence (average 56 keystrokes) with an FRR of 1.82% and an FAR of 1.94%. Compared with the scheme relying on only keystroke latency which has an FRR of 4.66%, an FAR of 17.92% and the required number of keystroke of 162, the proposed authentication system shows significant improvements in terms of accuracy, efficiency, and usability.

UR - http://www.scopus.com/inward/record.url?scp=85049797604&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85049797604&partnerID=8YFLogxK

U2 - 10.1109/WIFS.2017.8267642

DO - 10.1109/WIFS.2017.8267642

M3 - Conference contribution

VL - 2018-January

SP - 1

EP - 6

BT - 2017 IEEE Workshop on Information Forensics and Security, WIFS 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -