Continuous Authentication with Keystroke Dynamics

In this chapter we will discuss how keystroke dynamics can be used for true continuous authentication.We have collected keystroke dynamics data of 53 participants who used the computer freely and we have analysed the collected data. We will describe a system that decides on the genuineness of the user based on each and every single keystroke action of the current user and we will represent the results in a new manner. The continuous authentication system will lock out a user if the trust in genuineness of the current user is too low. Ideally such a system would never lock out a genuine user and detect an impostor user within as few keystroke actions as possible.

[1]  Patrick Bours.  Continuous keystroke dynamics: A different perspective towards biometric evaluation , 2012, Inf. Secur. Tech. Rep..

[2]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[3]  Jiri Matas,et al.  On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Ahmed Awad E. Ahmed,et al.  A New Biometric Technology Based on Mouse Dynamics , 2007, IEEE Transactions on Dependable and Secure Computing.

[5]  Lee Luan Ling,et al.  User authentication through typing biometrics features , 2005 .

[6]  James S. Okolica,et al.  User identification and authentication using multi-modal behavioral biometrics , 2014 .

[7]  Sung-Hyuk Cha,et al.  An investigation of keystroke and stylometry traits for authenticating online test takers , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[8]  Steven Furnell,et al.  A Long-term Trial of Keystroke Profiling using Digraph, Trigraph and Keyword Latencies , 2004, SEC.

[9]  S. J. Shepherd.  Continuous authentication by analysis of keyboard typing characteristics , 1995 .

[10]  R. Bergner.  What is behavior? And so what? , 2011 .

[11]  Issa Traoré,et al.  Biometric Recognition Based on Free-Text Keystroke Dynamics , 2014, IEEE Transactions on Cybernetics.

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

[13]  Patrick Bours,et al.  Continuous Authentication using Biometric Keystroke Dynamics , 2009 .

[14]  Damon L. Woodard,et al.  Biometric Authentication and Identification using Keystroke Dynamics: A Survey , 2012 .

[15]  Ian T. Nabney,et al.  Netlab: Algorithms for Pattern Recognition , 2002 .

[16]  Kathryn Hempstalk,et al.  Continuous Typist Verification using Machine Learning , 2009 .

[17]  Soumik Mondal,et al.  Continuous authentication using mouse dynamics , 2013, 2013 International Conference of the BIOSIG Special Interest Group (BIOSIG).

[18]  Sahin Albayrak,et al.  Continuous and non-intrusive identity verification in real-time environments based on free-text keystroke dynamics , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[19]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[20]  Mahdi Vasighi,et al.  A MATLAB toolbox for Self Organizing Maps and supervised neural network learning strategies , 2012 .

[21]  David V. Lu,et al.  Continuous Identity Verification through Keyboard Biometrics , 2005 .

[22]  Claudia Picardi,et al.  User authentication through keystroke dynamics , 2002, TSEC.

[23]  Thai Hoang Le,et al.  Keystroke Dynamics Extraction by Independent Component Analysis and Bio-matrix for User Authentication , 2010, PRICAI.

[24]  Arun Ross,et al.  Information fusion in biometrics , 2003, Pattern Recognit. Lett..

[25]  R. Ramnath,et al.  Physical Access Protection using Continuous Authentication , 2008, 2008 IEEE Conference on Technologies for Homeland Security.