Abstract
A user identification system which matches the keystroke dynamics of the users with the Cognitive RAM (CogRAM) weightless neural net is discussed in this paper. The keystroke patterns are made up of a common password for all users. While there are several common approaches to represent the users’ keystroke patterns, the approach adopted here is based on the force applied to each key. Effectively, they will then constitute a fixed length passkey. In addition, the system was developed based on an 8-bit AVR enhanced, RISC microcontroller. From the experimental results obtained, it can be seen that the identity of the users can be successfully matched just from their keystroke biometric patterns alone.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Gaines RS, Lisowski W, Press SJ, Shapiro N (1980) Authentication by keystroke timing: some preliminary results, Technical report R-2526-NSF, RAND Corporation Santa Monica, California, USA
Teh PS, Teoh ABJ, Yue S (2013) A Survey of Keystroke Dynamics Biometrics. Sci World J 2013:24
Joyce R, Gupta G (1990) Identity authentication based on keystroke latencies. Comm ACM 33:168–176
Monrose F, Rubin A (1997) Authentication via keystroke dynamics, Proceedings of the fourth ACM conference on computer and communications security, Zurich, Switzerland, p 48–56
De Ru W, Eloff J (1997) Enhanced password authentication through fuzzy logic. IEEE Expert 12:38–45
Obaidat MS, Sadoun B (1997) Verification of computer users using keystroke dynamics. IEEE Trans Syst Man Cybern 27:261–269
Tee ER, Selvanathan N (1996) Pin signature verification using wavelet transform. Malays J Comput Sci 9(2):71–78
Maisuria LK, Ong CS, Lai WK (1999) A comparison of artificial neural networks and cluster analysis for typing biometrics authentication, Proceedings of the international joint conference on neural networks (IJCNN), Washington, DC, 10–16 July 1999
Loy CC, Lim CP, Lai WK (2005) Pressure-based typing biometrics user authentication using the fuzzy ARTMAP neural network, Proceedings of the twelfth international conference on neural information processing (ICONIP 2005), Taipei, Taiwan ROC, p 647–652, 30 Oct–2 Nov 2005
Eltahir WE, Salami MJE, Ismail AF, Lai WK (2008) Design and evaluation of a pressure-based typing biometric authentication system. EURASIP J Inf Secur 2008(345047):14. doi:10.1155/2008/345047
Yong S, Lai WK, Coghill GG (2004) Weightless neural networks for typing biometrics authentication, Proceedings of the 8th international conference on knowledge-based intelligent information & engineering systems, KES’2004, vol II, Wellington, New Zealand, p 284–293, 22–24 Sept 2004
Obaidat MS, Sadoun B (1996) Keystroke dynamics based authentication. In: Jain AK, Bolle R, Pankanti S (eds) Biometrics: personal identification in networked society. Chapter 10, p 213–229, Springer, U.S.
Maxion RA, Killourhy KS (2010) Keystroke biometrics with number-pad input, Proceedings of IEEE/IFIP international conference on dependable systems and networks p 201–209
Aleksander I, De Gregorio M, Franca FMG, Lima PMV, Morton H (2009) A brief introduction to weightless neural systems, proceedings of European symposium on artificial neural networks. Bruges, Belgium
Force sensing resistor. http://en.wikipedia.org/wiki/Force-sensing_resistor. Accessed on 18 Mar 2015
Rumelhart DE, Hinton GE, William RJ (1986) Learning internal representation by error propagation. In: Parallel distributed processing: explorations in the microstructures of cognition, vol 1, MIT Press, Cambridge, MA
Ludermir TB et al (1999) Weightless neural models: a review of current and past works. Neural Comput Surv 2:41–60
Kan WK, Aleksander I (1987) A probabilistic logic neuron network for associative learning, Proc. IEEE 1st Int Conf Neural Networks II:541–548, San Diego, June 1987
ECDBC F, Fairhurst MC, Bisset DL (1991) Adaptive pattern recognition using goal seeking neurons. Pattern Recogn Lett 12:131–138
Bowmaker RG, Coghill GG (1992) Improved recognition capabilities for goal seeking neuron. Electron Lett 28(3):220–221
Yee P, Coghill GG (2004) Weightless neural networks: a comparison between the discriminator and the deterministic adaptive RAM network, KES 2004:319–328
Lai WK, Tan BG, Soo MS, Khan I (2014) Two-factor user authentication with the CogRAM weightless neural net, World Congr Comput Intell (WCCI 2014), 6–11 July 2014, Beijing, China
Patel ND, Nguang SK, Coghill GG (2007) Neural network implementation using bit streams. IEEE Trans Neural Networks 18(5):1488–1504
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Lai, W.K., Tan, B.G., Soo, M.S., Khan, I. (2016). User Identification of Keystroke Biometric Patterns with the Cognitive RAM Weightless Neural Net. In: Soh, P., Woo, W., Sulaiman, H., Othman, M., Saat, M. (eds) Advances in Machine Learning and Signal Processing. Lecture Notes in Electrical Engineering, vol 387. Springer, Cham. https://doi.org/10.1007/978-3-319-32213-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-32213-1_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-32212-4
Online ISBN: 978-3-319-32213-1
eBook Packages: EngineeringEngineering (R0)