Rhu Keystroke Touchscreen Benchmark

Biometric systems are currently widely used in many applications to control and verify individual's identity. Keystroke dynamics modality has been shown as a promising solution that would be used in many applications such as e-payment and banking applications. However, such systems suffer from several performance limitations (such as cross-devices problem) that prevent their widespread of use in real applications. The objective of this paper is to provide researchers and developers with a public touchscreen-based benchmark collected using a mobile phone and a tablet (both portrait and landscape orientation each). Such a benchmark can be used to assess keystroke-based matching algorithms. Furthermore, It is mainly developed to measure the robustness of keystroke matching algorithms vis-'a-vis cross-devices and orientation variations. An online visualizer for the database is also given to researchers allowing them to visualize the acquired keystroke signals.

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

[2]  Claudia Picardi,et al.  Keystroke analysis of free text , 2005, TSEC.

[3]  Roy A. Maxion,et al.  Comparing anomaly-detection algorithms for keystroke dynamics , 2009, 2009 IEEE/IFIP International Conference on Dependable Systems & Networks.

[4]  Gopal K. Gupta,et al.  Identity authentication based on keystroke latencies , 1990, Commun. ACM.

[5]  Christophe Rosenberger,et al.  Keystroke dynamics with low constraints SVM based passphrase enrollment , 2009, 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems.

[6]  J. J. Higgins Introduction to Modern Nonparametric Statistics , 2003 .

[7]  Yan Lindsay Sun,et al.  Shared keystroke dataset for continuous authentication , 2016, 2016 IEEE International Workshop on Information Forensics and Security (WIFS).

[8]  Dario Maio,et al.  Synthetic fingerprint-database generation , 2002, Object recognition supported by user interaction for service robots.

[9]  Masaki Hashiyada,et al.  Development of biometric DNA ink for authentication security. , 2004, The Tohoku journal of experimental medicine.

[10]  Jugurta R. Montalvão Filho,et al.  On the equalization of keystroke timing histograms , 2006, Pattern Recognit. Lett..

[11]  Ting-Yi Chang,et al.  Two novel biometric features in keystroke dynamics authentication systems for touch screen devices , 2014, Secur. Commun. Networks.

[12]  Daw-Tung Lin Computer-access authentication with neural network based keystroke identity verification , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

[13]  Stergios B. Fotopoulos,et al.  Introduction to Modern Nonparametric Statistics , 2004, Technometrics.

[14]  Danoush Hosseinzadeh,et al.  Gaussian Mixture Modeling of Keystroke Patterns for Biometric Applications , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[15]  Baochang Zhang,et al.  Study on the BeiHang Keystroke Dynamics Database , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[16]  Baptiste Hemery,et al.  Performance Evaluation of Behavioral Biometric Systems , 2010 .

[17]  Prudhvi Gurram,et al.  Exploiting polarization-state information for cross-spectrum face recognition , 2015, 2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS).

[18]  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.

[19]  Mohamad El-Abed,et al.  RHU Keystroke: A mobile-based benchmark for keystroke dynamics systems , 2014, 2014 International Carnahan Conference on Security Technology (ICCST).

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

[21]  Mohammad S. Obaidat,et al.  Verification of computer users using keystroke dynamics , 1997, IEEE Trans. Syst. Man Cybern. Part B.

[22]  Stephanie Schuckers,et al.  Shared research dataset to support development of keystroke authentication , 2014, IEEE International Joint Conference on Biometrics.

[23]  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.

[24]  Lee Luan Ling,et al.  Biometric Access Control Through Numerical Keyboards Based on Keystroke Dynamics , 2006, ICB.

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

[26]  Kenneth Revett,et al.  On the Use of Rough Sets for User Authentication Via Keystroke Dynamics , 2007, EPIA Workshops.

[27]  Shan Juan Xie,et al.  New Trends and Developments in Biometrics , 2012 .

[28]  John J. Leggett,et al.  Dynamic Identity Verification via Keystroke Characteristics , 1991, Int. J. Man Mach. Stud..

[29]  Sharath Pankanti,et al.  Biometrics: a grand challenge , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..