Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Pattern Analysis and Applications
Published in: Pattern Analysis and Applications 1/2011

01-02-2011 | Theoretical Advances

A multiple layer fusion approach on keystroke dynamics

Authors: Pin Shen Teh, Andrew Beng Jin Teoh, Connie Tee, Thian Song Ong

Published in: Pattern Analysis and Applications | Issue 1/2011

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In this paper, we present a novel keystroke dynamic recognition system by means of a novel two-layer fusion approach. First, we extract four types of keystroke latency as the feature from our dataset. The keystroke latency will be transformed into similarity scores via Gaussian Probability Density Function (GPD). We also propose a new technique, known as Direction Similarity Measure (DSM), which measures the absolute difference between two sets of latency. Last, four fusion approaches coupled with six fusion rules are applied to improve the final result by combining the scores that are produced by GPD and DSM. Best result with equal error rate of 1.401% is obtained with our two-layer fusion approach.
previous article Shape feature descriptor using modified Zernike moments
next article Efficient on-line signature recognition based on multi-section vector quantization

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
Obaidat MS, Sadoun B (1999) Keystroke dynamics based authentication. Biometrics. Springer, New York, pp 213–229
2.
Joyce R, Gupta G (1990) Identity authentication based on keystroke latencies. Commun ACM 33(2):168–176CrossRef
3.
De Ru WG, Eloff JHP (1997) Enhanced password authentication through fuzzy logic. IEEE Expert Intell Syst Appl 12(6):38–45
4.
Gaines R, Lisowski W, Press S, Shapiro N (1980) Authentication by keystroke timing: some preliminary results, The Rand Report R-256-NSF. Rand Corporation, Santa Monica
5.
Monrose F, Rubin AD (2000) Keystroke dynamics as a biometric for authentication. Future Gener Comput Syst 16(4):351–359CrossRef
6.
D’Souza DC (2002) Typing dynamics biometric authentication. Department of Information Technology and Electrical Engineering. University of Queensland, Bachelor of Engineering in the Division of Software Engineering
7.
RN Rodrigues, GFG Yared et al (2005) Biometric access control through numerical keyboards based on keystroke dynamics, vol 3832. Springer, Berlin, pp 640–646
8.
Hosseinzadeh D, Krishnan S et al (2006) Keystroke identification based on Gaussian mixture models. In: IEEE international conference on acoustics, speech and signal processing. Toulouse, France, pp 1144–1147
9.
Lv HR, Wang WY (2006) Biologic verification based on pressure sensor keyboards and classifier fusion techniques. IEEE Trans Consum Electr 52(3):1057–1063CrossRefMathSciNet
10.
Loy CC, Lai WK et al (2007) Keystroke patterns classification using the ARTMAP-FD neural network. In: Third international conference on intelligent information hiding and multimedia signal processing, vol 1, pp 61–64
11.
Hocquet S, Ramel J-Y et al (2007) User classification for keystroke dynamics authentication. In: Advances in biometrics, vol 4642. Springer, Berlin, pp 531–539
Metadata
Title
A multiple layer fusion approach on keystroke dynamics
Authors
Pin Shen Teh
Andrew Beng Jin Teoh
Connie Tee
Thian Song Ong
Publication date
01-02-2011
Publisher
Springer-Verlag
Published in
Pattern Analysis and Applications / Issue 1/2011
Print ISSN: 1433-7541
Electronic ISSN: 1433-755X
DOI
https://doi.org/10.1007/s10044-009-0167-9

Other articles of this Issue 1/2011

Pattern Analysis and Applications 1/2011 Go to the issue

Theoretical Advances

Preserving spatial information and overcoming variations in appearance for face recognition

Theoretical Advances

Shape feature descriptor using modified Zernike moments

Theoretical Advances

Identification of unreliable segments to improve skeletonization of handwriting images

Theoretical Advances

A new hybrid method for gene selection

Theoretical Advances

Robust scale invariant target detection using the scale-space theory and optimization for IRST

Theoretical Advances

A sparse multinomial probit model for classification

Premium Partner

    Image Credits