Abstract
The design and development of a real-time enhanced password security system, based on the analysis of habitual typing rhythms of individuals, is discussed in this paper. The paper examines the use of force exerted on the keyboard and time latency between keystrokes to create typing patterns for individual users. Pressure signals which are taken from the sensors underneath the keypad are extracted accordingly. These are then used to recognize authentic users and reject imposters. An experimental setup has been developed to capture the pressure signal information of the users’ typing rhythm. Neuro-fuzzy system is employed as the classifier to measure the user’s typing pattern using the Adaptive Neural Fuzzy Inference System toolbox (ANFIS) in MATLAB.
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References
De Ru, W.G., Eloff, J.H.P.: Enhanced Password Authentication through Fuzzy Logic. IEEE Expert 12(6), 38–45 (1997)
Wong, F.M.H., Ainil Sufreena, M.S., Faris, A., Lai, W.K., Ong, C.S.: Enhanced User Authentication Through Typing Biometrics with Artificial Neural Network and K-Nearest Neighbor Algorithm. In: Proc. 35th Asilomar Conference on Systems, Signal and Computers, California USA, pp. 1–3 (2002)
Yong, Z., Tan, T., Wang, Y.H.: Biometric Personal Identification Based on Iris Patterns. National Laboratory of Pattern Recognition, Beijing (1999)
Kwan, H.K., Cai, Y.: A Fuzzy Neural Network and its Application to Pattern Recognition. IEEE Transactions on Fuzzy Systems 2(3) (August 1994)
Garzon, M.H., Ankaraju, P., Evan, D., Kozma, R.: Neurofuzzy Recognition and Generation of Facial Features in Talking Heads. Computer Science, Memphis
Jang, S.R.: ANFIS: Adaptive Network Based Fuzzy Inference Systems. IEEE Transactions on System, Man and Cybernatics 23(3), 665–685 (1993)
Jang, J.S., Gulley, N.: Fuzzy Logic Toolbox for use with MATLAB. In: The Mathworks, INC., Natick, MA (1995)
Jang, J.S., Sun, C.T.: Neuro-Fuzzy Modeling and Control. Proc. Of the IEEE 83(3), 378–406 (1995)
Chin, T.L., Lee George, C.S.: A Neuro-Fuzzy Synergism to Intelligent Systems, pp. 661–670. Prentice Hall, Englewood Cliffs (1995)
Lefteri, H.T., Robert, E.U.: Fuzzy and Neural Approaches in Engineering, p. 471. John Wiley & Sons, Inc., Chichester (1997)
Bezdek, J.C., Pal, S.K. (eds.): Fuzzy Models for Pattern Recognition. IEEE Press, Piscataway (1992)
Kandel, A.: Fuzzy Techniquess in Pattern Recognition. Wiley, New York (1982)
Yamakawa, T., Tomoda, S.: A Fuzzy Neuron and its Application to Pattern Recognition. In: Proc. Third Int. Fuzzy System Associat. Congress Japan, pp. 30–38 (1989)
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Dahalan, A., Salami, M.J.E., Lai, W.K., Ismail, A.F. (2004). Intelligent Pressure-Based Typing Biometrics System. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30133-2_38
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DOI: https://doi.org/10.1007/978-3-540-30133-2_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23206-3
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