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Fingerprint Image Encryption Using a 2D Chaotic Map and Elliptic Curve Cryptography
Abstract:Fingerprints are suitable as long-term markers of human identity since they provide detailed and unique individual features which are difficult to alter and durable over life time. In this paper, we propose an algorithm to encrypt and decrypt fingerprint images by using a specially designed Elliptic Curve Cryptography (ECC) procedure based on block ciphers. In addition, to increase the confusing effect of fingerprint encryption, we also utilize a chaotic-behaved method called Arnold Cat Map (ACM) for a 2D scrambling of pixel locations in our method. Experimental results are carried out with various types of efficiency and security analyses. As a result, we demonstrate that the proposed fingerprint encryption/decryption algorithm is advantageous in several different aspects including efficiency, security and flexibility. In particular, using this algorithm, we achieve a margin of about 0.1% in the test of Number of Pixel Changing Rate (NPCR) values comparing to the-state-of-the-art performances.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1474867Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 483
 N. Koblitz, “Elliptic Curve Cryptography” Mathematics of Computation, AMS, vol. 48, no. 177, pp. 203-208, 1987.
 V. Miller, “Uses of Elliptic Curve in Cryptography”, Advanced in Cryptology, Springer-Verlag vol. 85, pp. 417-426, 1986.
 A. K. Jain, K. Nandakumar, A. Nagar, “Biometric template security”, Advances in Signal Process, EURASIP journal, vol. 2008, pp. 1-17, 2008.
 G. Panchal and D. Samanta, “A novel Approach to Fingerprint Biometric-Based Cryptographic Key Generation and its Application to storage security”, Computer and Electrical Engineering 000, Elsevier, pp. 1-18, 2018.
 C. Moujahdi, G. Bebis, S. Ghouzali and M. Rizza, “Fingerprint shell: Secure representation of fingerprint template”, Pattern Recognition Letters 24, Elsevier, pp. 189-196, 2014.
 F. Han, J. Hu, X. Yu and Y. Wang, “Fingerprint image encryption via multi-scroll chaotic attractors”, Applied Mathematics and Computation 185, Elsevier, pp. 931-939, 2007.
 Haiyong Chen and Hailiang Chen, “A novel algorithm of fingerprint encryption using minutiae-based transformation”, Pattern Recognition Letters 32, Elsevier, pp. 305-309, 2011.
 S. Zhao, H. Li and X. Yan, “A secure and efficient fingerprint image encryption scheme”, The 9th International Conference for Young Computer Scientists, IEEE Computer Society, P.R.C, pp. 2803-2808, 2008.
 G. Mehta, M. K. Dutta, J. Karasek and P. S. Kim, “An efficient and lossless fingerprint encryption algorithm using Henon Map & Arnold Transformation”, International Conference on Control Communication and Computing, IEEE, pp. 485-48, 2013.
 H-I Hsiao and J. Lee, “Fingerprint image cryptography based on multiple chaotic system”, Signal Processing 131, Elsevier, pp. 169-181, 2015.
 ECC Brainpool Standard Curves and Curve Generation v.1.0, 19.10.2005
 Institute of Automation, Chinese Academy of Sciences(CASIA), Biometric ideal test, Accessed 10 January 2017,
 O. Reyad and Z. Kotulski, Image “encryption using Koblitz’s encoding and new mapping method based on elliptic curve random number generator”, Springer International Publishing, Switzerland, 2015, pp. 34-45.
 D. Hankerson, A. Menezes and S. Vanstone, “Guide to Elliptic Curve Cryptography”, Springer, 2004.
 Y. Wu, P. Noonan and S. Agaian, “UPCR and UACI randomness test for image encryption”, Cyber Journal: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunicstion (JSAT), pp. 31-38, April Edition, 2011.
 Y. Wu, G. Yang, H. Jin and J.P. Noonan, “Image encryption using the two dimensional logistic chaotic map”, Journal of Electronic Imaging, vol. 21(1), 013014, March, 2012.
 S. Toughi, M. H. fathi and Y. A. Sekhavet,, “An image encryption scheme based on elliptic curve pseudo random and Advanced encryption system”, Signal processing, vol. 141, Elsevier, pp. 217-227, 2017.
 X. Wang, X. Zhu and Y. Zhang, “An image encryption algorithm based on Josephus Traversing and mixed chaotic map”, IEEE, 2018.