Analysis of Keystroke Dynamics for the Generation of Synthetic Datasets

Biometrics is an emerging technology more and more present in our daily life. However, building biometric systems requires a large amount of data that may be difficult to collect. Collecting such sensitive data is also very time consuming and constrained, s.a. GDPR legislation. In the case of keystroke dynamics, existing databases have less than 200 users. For these reasons, we aim at generating a keystroke dynamics synthetic dataset. This paper presents the generation of keystroke data from known users as a first step towards the generation of synthetic datasets, and could also be used to impersonate users' identity.

[1]  Karl Pearson F.R.S..  LIII. On lines and planes of closest fit to systems of points in space , 1901 .

[2]  Yang Gao,et al.  Enhanced free-text keystroke continuous authentication based on dynamics of wrist motion , 2017, 2017 IEEE Workshop on Information Forensics and Security (WIFS).

[3]  Fabian Monrose,et al.  Keystroke dynamics as a biometric for authentication , 2000, Future Gener. Comput. Syst..

[4]  Jean-Yves Ramel,et al.  User Classification for Keystroke Dynamics Authentication , 2007, ICB.

[5]  Raffaele Cappelli,et al.  SFinGe : an Approach to Synthetic Fingerprint Generation , 2004 .

[6]  Baptiste Hemery,et al.  Computation EvaBio: A Tool for Performance Evaluation in Biometrics , 2011 .

[7]  Norman Shapiro,et al.  Authentication by Keystroke Timing: Some Preliminary Results , 1980 .

[8]  Hyoungjoo Lee,et al.  Retraining a keystroke dynamics-based authenticator with impostor patterns , 2007, Comput. Secur..

[9]  Christophe Rosenberger,et al.  GREYC keystroke: A benchmark for keystroke dynamics biometric systems , 2009, 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems.

[10]  Christophe Rosenberger,et al.  A review on the public benchmark databases for static keystroke dynamics , 2015, Comput. Secur..

[11]  Baptiste Hemery,et al.  Unconstrained keystroke dynamics authentication with shared secret , 2011, Comput. Secur..

[12]  Andrew Beng Jin Teoh,et al.  Biohashing: two factor authentication featuring fingerprint data and tokenised random number , 2004, Pattern Recognit..

[13]  Kenneth Revett,et al.  A machine learning approach to keystroke dynamics based user authentication , 2007, Int. J. Electron. Secur. Digit. Forensics.

[14]  B. Hussien,et al.  Computer-Access Security Systems Using Keystroke Dynamics , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Fabian Monrose,et al.  Authentication via keystroke dynamics , 1997, CCS '97.

[16]  Christophe Rosenberger,et al.  Keystroke Dynamics Overview , 2011 .

[17]  Gang Hua,et al.  Labeled Faces in the Wild: A Survey , 2016 .

[18]  Roy A. Maxion,et al.  Should Security Researchers Experiment More and Draw More Inferences? , 2011, CSET.

[19]  Christophe Rosenberger,et al.  Web-Based Benchmark for Keystroke Dynamics Biometric Systems: A Statistical Analysis , 2012, 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[20]  David Umphress,et al.  Identity Verification Through Keyboard Characteristics , 1985, Int. J. Man Mach. Stud..

[21]  Soumik Mondal,et al.  A study on continuous authentication using a combination of keystroke and mouse biometrics , 2017, Neurocomputing.