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A Study On Fingerprint Hash Code Generation Based On Md5 Algorithm And Freeman Chain Code

Authors: K. Krishna Prasad; P. S. Aithal;

A Study On Fingerprint Hash Code Generation Based On Md5 Algorithm And Freeman Chain Code

Abstract

{"references": ["1.\tNandakumar, K., Jain, A. K., & Nagar, A. (2008). Biometric template security. Eurasip Journal on Advances in Signal Processing. https://doi.org/10.1155/2008/579416. 2.\tNandakumar, K., & Jain, A. K. (2004). Local Correlation-based Fingerprint Matching. In ICVGIP (pp. 503-508). 3.\tKrishna Prasad, K. & Aithal, P.S. (2017). A Conceptual Study on Image Enhancement Techniques for Fingerprint Images. International Journal of Applied Engineering and Management Letters (IJAEML), 1(1), 63-72. DOI: http://dx.doi.org/10.5281/zenodo.831678. 4.\tKrishna Prasad, K. & Aithal, P.S. (2017). Literature Review on Fingerprint Level 1 and Level 2 Features Enhancement to Improve Quality of Image. International Journal of Management, Technology, and Social Sciences (IJMTS), 2(2), 8-19. DOI: http://dx.doi.org/10.5281/zenodo.835608. 5.\tKrishna Prasad, K. & Aithal, P.S. (2017). Fingerprint Image Segmentation: A Review of State of the Art Techniques. International Journal of Management, Technology, and Social Sciences (IJMTS), 2(2), 28-39. DOI: http://dx.doi.org/10.5281/zenodo.848191. 6.\tKrishna Prasad, K. & Aithal, P.S. (2017). A Novel Method to Contrast Dominating Gray Levels during Image contrast Adjustment using Modified Histogram Equalization. International Journal of Applied Engineering and Management Letters (IJAEML), 1(2), 27-39. DOI: http://dx.doi.org/10.5281/zenodo. 896653. 7.\tKrishna Prasad, K. & Aithal, P.S. (2017).Two Dimensional Clipping Based Segmentation Algorithm for Grayscale Fingerprint Images. International Journal of Applied Engineering and Management Letters (IJAEML), 1(2), 51-65. DOI: http://dx.doi.org/10.5281/zenodo.1037627. 8.\tKrishna Prasad, K. & Aithal, P.S. (2017). A conceptual Study on Fingerprint Thinning Process based on Edge Prediction. International Journal of Applied Engineering and Management Letters (IJAEML), 1(2), 98-111. DOI: http://dx.doi.org/10.5281/zenodo.1067110. 9.\tKrishna Prasad, K. (2017). A Critical Study on Fingerprint Image Sensing and Acquisition Technology. International Journal of Case Studies in Business, IT and Education (IJCSBE), 1(2), 86-92. DOI: http://dx.doi.org/10.5281/zenodo.1130581. 10.\tTulyakov, S., Farooq, F., Mansukhani, P., & Govindaraju, V. (2007). Symmetric hash functions for secure fingerprint biometric systems. Pattern Recognition Letters, 28(16), 2427-2436. 11.\tGonzalez, R. C., & Woods, R. E. (1992). Digital image processing. 12.\tBernard, M., Fromont, E., Habrard, A., & Sebban, M. (2012, June). Handwritten digit recognition using edit distance-based KNN. In Teaching Machine Learning Workshop. 13.\tJuels, A. (2002). M. Sudan 'A fuzzy vault scheme'. In Proceedings of the 2002 IEEE International Symposium on Information Theory (Vol. 408). 14.\tTuyls, P., Akkermans, A. H., Kevenaar, T. A., Schrijen, G. J., Bazen, A. M., & Veldhuis, R. N. (2005, July). Practical biometric authentication with template protection. In AVBPA (Vol. 3546, pp. 436-446). 15.\tHolst, J. C., & Draper, D. A. (1999). U.S. Patent No. 5,999,039. Washington, DC: U.S. Patent and Trademark Office. 16.\tDavida, G. I., Frankel, Y., Matt, B., & Peralta, R. (1999). On the relation of error correction and cryptography to an online biometric based identification scheme. In Workshop on coding and cryptography. 17.\tHao, F, Anderson, R & Daugman, J 2006, Combining Crypto with Biometrics Effectively', IEEE Transactions on Computers, vol. 55, pp. 1081-1088. 18.\tKelkboom, E. J., G\u00f6kberk, B., Kevenaar, T. A., Akkermans, A. H., & van der Veen, M. (2007, August). \"3D face\": biometric template protection for 3D face recognition. In International Conference on Biometrics (pp. 566-573). Springer, Berlin, Heidelberg. 19.\tConnie, T., Teoh, A., Goh, M., & Ngo, D. (2005). Palm Hashing: a novel approach for cancelable biometrics. Information processing letters, 93(1), 1-5. 20.\thttps://hackaday.com/2015/11/10/your-unhashable-fingerprints-secure-nothing/, Last Accesses Date: 05-12-2017. 21.\thttps://security.stackexchange.com/questions/42384/is-there-any-way-to-cryptographically-hash-a-human-thumbprint, Last Accesses Date: 05-12-2017. 22.\tChikkerur, S. S. (2005). Online fingerprint verification system (p. 2005). State University of New York at Buffalo. 23.\tBhuyan, M. H., Saharia, S., & Bhattacharyya, D. K. (2012). An effective method for fingerprint classification. arXiv preprint arXiv:1211.4658. 24.\tMeng, X. P., Wu, Z. G., & Zhao, Y. L. (2009). Algorithm of fingerprint identification based on fingerprint texture structure [J]. Computer Engineering and Design, 13, 031. 25.\tAithal, P. S. (2016). A Review on Advanced Security Solutions in Online Banking Models, International Journal of Scientific Research and Modern Education (IJSRME), 1(1), 421-429. DOI: http://doi.org/10.5281/zenodo.160971. 26.\tAithal, P. S. (2015). Biometric Authenticated Security Solution to Online Financial Transactions. International Journal of Management, IT and Engineering (IJMIE), 5(7), 455-464, DOI: http://doi.org/10.5281/zenodo.268875."]}

The drastic changes in mobile and wireless based technologies and increasing number of applications and users demanded high-security concern, which leads to research on biometrics with a purpose to increase the security aspects and to minimize security threats. The current global mindset toward terrorism has influenced people and their governments to take some special actions and be extra proactive in protection or security problems. Fingerprint image and identification technology have been in life for hundreds of years. Archaeologists have exposed proof suggesting that interest in fingerprints dates to prehistory. But the modern study reveals that fingerprint is not so secured like secured passwords which consist of alphanumeric characters, number and special characters. Fingerprints are left at crime places, on materials or at the door which is usually class of latent fingerprints. We cannot keep fingerprint as secure like rigid passwords. In this paper, we discuss fingerprint image Hash code generation based on the MD5 Algorithm and Freeman Chain code calculated on the binary image. Freeman chain code extracts all possible boundaries for an image and which gives starting x and y positions as x0 and y0. Hashcode alone not sufficient for Verification or Authentication purpose, but can work along with Multifactor security model or it is half secured. To implement Hash code generation we use MATLAB2015a. This study shows how fingerprints Hash code uniquely identifies a user or acts as index-key or identity-key.

Related Organizations
Keywords

Fingerprint Image, Fingerprint Hashcode, Authentication, Multifactor Authentication Model, Freeman Chain Code & MD5 Algorithm

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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