Abstract
To improve the security and stability of biometric handwriting samples a Bio-Hash algorithm for handwriting was introduced in [1]. It utilizes features to describe how the sample was written, but the current set of features does not characterize the visual appearance of the sample itself. In this paper we present a set of new features derived from handwriting forensics and OCR algorithms to address this issue. Furthermore, here the security of the old and new sets of features is evaluated for their resilience against a new, fully automated attack trying to compute raw data matching a given hash vector.
The main contributions of this paper are: The introduction of new features with a potential to increase the attack resilience of the Bio-Hash algorithm, and, an improvement of the attack approach from [6] to produce more realistic looking synthetic handwriting signals.
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References
Vielhauer, C.: Biometric User Authentication for IT Security: From Fundamentals to Handwriting. Spinger, New York (2006)
Senior, A.W., Robinson, A.J.: An Off-Line Cursive Handwriting Recognition System. IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 309–321 (1998)
Bresenham, J.: Algorithm for computer control of a digital plotter. IBM Systems Journal 4 (1965)
Yanikoglu, B., Sanson, P.: Off-Line Cursive Handwriting Recognition Using Style Parameters, Dartmouth College, Computer Science, Version: 1993 (PCS-TR93-192) (1993), http://www.cs.dartmouth.edu/reports/TR93-192.ps.Z
Koppenhaver, K.: Forensic Document Examination: Principles and Practices. Humana Press (2007)
Kümmel, K., Vielhauer, C., Scheidat, T., Franke, D., Dittmann, J.: Handwriting Biometric Hash Attack: A Genetic Algorithm with User Interaction for Raw Data Reconstruction. In: De Decker, B., Schaumüller-Bichl, I. (eds.) CMS 2010. LNCS, vol. 6109, pp. 178–190. Springer, Heidelberg (2010)
Makrushin, A., Scheidat, T., Vielhauer, C.: Improving reliability of biometric hash generation through the selection of dynamic handwriting features. In: Shi, Y.Q., Katzenbeisser, S. (eds.) Transactions on DHMS VIII. LNCS, vol. 7228, pp. 19–41. Springer, Heidelberg (2012)
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Hasselberg, A., Zimmermann, R., Kraetzer, C., Scheidat, T., Vielhauer, C., Kümmel, K. (2013). Security of Features Describing the Visual Appearance of Handwriting Samples Using the Bio-hash Algorithm of Vielhauer against an Evolutionary Algorithm Attack. In: De Decker, B., Dittmann, J., Kraetzer, C., Vielhauer, C. (eds) Communications and Multimedia Security. CMS 2013. Lecture Notes in Computer Science, vol 8099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40779-6_6
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DOI: https://doi.org/10.1007/978-3-642-40779-6_6
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