Abstract
We show an architecture to automatically generate cryptographic keys using the FingerCode as defined by Jain et al. [4]. The FingerCode is obtained from gray scale fingerprint images. The architecture uses a classifier to compensate for the natural variability on the FingerCodes. In a training step the FingerCodes of the fingerprint samples for registered users are obtained; then random binary codes are assigned to each set of FingerCodes from the same finger, and finally an array of Support Vector Machines (SVM) is trained to associate the FingerCodes to their assigned random binary key. Each SVM is independent and assigns one bit, allowing the construction of binary keys of arbitrary length by adding and training more SVMs. To test the system, different set of fingerprint images from the same fingers used on the training step were used. The FingerCodes were calculated used as input to the SVM array to generate the assigned keys. Experimental results obtained using fingerprints selected from the FVC2000 and FVC2002 databases show results up to 90% performance on generating valid keys.
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Ramírez-Ruiz, J.A., Pfeiffer, C.F., Nolazco-Flores, J.A. (2006). Cryptographic Keys Generation Using FingerCodes. In: Sichman, J.S., Coelho, H., Rezende, S.O. (eds) Advances in Artificial Intelligence - IBERAMIA-SBIA 2006. IBERAMIA SBIA 2006 2006. Lecture Notes in Computer Science(), vol 4140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11874850_22
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DOI: https://doi.org/10.1007/11874850_22
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