Intelligent Pressure-Based Typing Biometrics System

The design and development of a real-time enhanced password security system, based on theanalysis of habitual typing rhythms of individuals, is discussed in this paper. The paper examinesthe use of force exerted on the keyboard and time latency between keystrokes to create typingpatterns for individual users. Pressure signals which are taken from the sensors underneath thekeypad are extracted accordingly. These are then used to recognize authentic users and rejectimposters. An experimental setup has been developed to capture the pressure signal informationof the users' typing rhythm. Neuro-fuzzy system is employed as the classifier to measure theuser's typing pattern using the Adaptive Neural Fuzzy Inference System toolbox (ANFIS) inMATLAB. © Springer-Verlag 2004. References[1] Ru, W.G.D., Eloff, J.H.P.Enhanced Password Authentication through Fuzzy Logic(1997) IEEE Expert, 12 (6), pp. 38-45.[2] Wong, Fadhli, M.H., Ainil Sufreena, M.S., Fans, A., Lai, W.K., Ong, C.S.Enhanced User Authentication Through Typing Biometrics with Artificial NeuralNetwork and K-Nearest Neighbor Algorithm(2002) Proc. 35th Asilomar Conference on Systems, Signal and Computers CaliforniaUSA, pp. 13.[3] Yong, Z., Tan, T., Wang, Y.H.(1999) Biometrie Personal Identification Based on Iris Patterns, National Laboratory of Pattern Recognition, Beijing[4] Kwan, H.K., Cai, Y.A Fuzzy Neural Network and its Application to Pattern Recognition (1994) IEEE Transactions on Fuzzy Systems, volume 2, issue 3, pages 185-193,August 1994[5] Garzon, M.H., Ankaraju, P., Evan, D., Kozma, R. Neurofuzzy Recognition and Generation of Facial Features in Talking Heads,Computer Science, Memphis.[6] Lang, S.R.ANFIS: Adaptive Network Based Fuzzy Inference Systems(1993) IEEE Transactions on System, Man and Cybematics, 23 (3), pp. 665-685.[7] Jang, J.S., Gulley, N.(1995) Fuzzy Logic Toolbox for Use with MATLAB,the Mathworks, INC. Natick, MA[8] Jang, J.S., Sun, C.T.Neuro-Fuzzy Modeling and Control(1995) Proc. of the IEEE, 83 (3), pp. 378-406.March[9] Chin, T.L., Lee George, C.S.(1995) A Neuro-Fuzzy Synergism to Intelligent Systems,pp. 661-670. Prentice Hall[10] Lefteri, H.T., Robert, E.U.(1997) Fuzzy and Neural Approaches in Engineering,John Wiley & Sons, Inc.[11] (1992) Fuzzy Models for Pattern Recognition,J.C. Bezdek and S.K. Pal, Eds. Piscataway, NJ:EEE Press[12] Kandel, A.(1982) Fuzzy Techniquess in Pattern Recognition,New York: Wiley [13] Yamakawa, T., Tomoda, S.A Fuzzy Neuron and its Application to Pattern Recognition(1989) Proc. Third Int. Fuzzy System Associat. Congress Japan, p. 3038. Authors’ affiliationDA: Mechatronics Dept., Faculty of Engineering, International Islamic University Malaysia(HUM), Jalan Gombak, 53100 Kuala Lumpur, MalaysiaSMJE:Technology Research Group MIMOS Bhd, Technology Park Malaysia, 57000 KualaLumpur, Malaysia LWK; IAP: Faculty of Engineering International Islamic University Malaysia (HUM), JalanGombak, 53100 Kuala Lumpur, Malaysia Correspondence AddressDahalan A.; Mechatronics Dept., Faculty of Engineering, International Islamic UniversityMalaysia (HUM), Jalan Gombak, 53100 Kuala Lumpur, Malaysia; email: [email protected]