Document Type : Research Paper

Authors

1 Department of Computer Science, University of Technology, Baghdad, Iraq

2 College of Education Ibn Rushd, University of Baghdad, Baghdad, Iraq,

3 Department of Computer Science, University of Turath, Baghdad, Iraq,

Abstract

Biometrics are short of revocability and privacy while cryptography cannot adjust the user’s identity. By obtaining cryptographic keys using biometrics, one can obtain the features such as revocability, assurance about user’s identity, and privacy. Multi-biometrical based cryptographic key generation approach has been proposed, subsequently, left and right eye and ear of a person are uncorrelated from one to other, and they are treated as two independent biometrics and combine them in our system. None-the-less, the encryption keys are produced with the use of an approach of swarm intelligence. Emergent collective intelligence in groups of simple autonomous agents is collectively termed as a swarm intelligence. The Meerkat Clan Key Generation Algorithm (MCKGA) is a method for the generation of a key stream for the encryption of the plaintext. This method will reduce and distribute the number of keys. Testing of system, it was found that the keys produced by the characteristics of the eye are better than the keys produced by the characteristics of the ear. The advantages of our approach comprise generation of strong and unique keys from users’ biometric data using MCKGA and it is faster and accurate in terms of key generation.

Keywords

[1] A. Ross and P. Flynn, Handbook of biometrics. Springer Science+ Business Media, LLC, 2008
[2] Y. C. Feng, P. C. Yuen, and A. K. Jain, “A hybrid approach for face template protection,” in Biometric Technology for Human Identification V, 2008, vol. 6944, p. 694408.
[3] P. Balakumar and R. Venkatesan, “A survey on biometrics based cryptographic key generation schemes,” Int. J. Compute. Sci. Inf. Technol. Secur., vol. 2, no. 1, pp. 80–85, 2012.
[4] P. Balakumar and R. Venkatesan, “A survey on biometrics based cryptographic key generation schemes,” Int. J. Compute. Sci. Inf. Technol. Secur., vol. 2, no. 1, pp. 80–85, 2012.
[5] Biggio, “Adversarial Pattern Classification,” Doctoral dissertation, Sardinia Univ. Cagliari, 2010.
[6] D. D. Salman, R. A. Azeez, and A. J. AH, “BUILD CRYPTOGRAPHIC SYSTEM FROM MULTI-BIOMETRICS USING MEERKAT ALGORITHM”, Iraqi Journal for Computers and Informatics, Vol 45, Issue 2, 2019.
[7] Y.-J. Chang, W. Zhang, and T. Chen, “Biometrics-based cryptographic key generation,” in 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No. 04TH8763), 2004, vol. 3, pp. 2203–2206.
[8] Juels and M. Sudan, “A fuzzy vault scheme,” Des. Codes Crypto. vol. 38, no. 2, pp. 237–257, 2006.
[9] Y. Dodis, L. Reyzin, and A. Smith, “Fuzzy extractors: How to generate strong keys from biometrics and other noisy data,” in International conference on the theory and applications of cryptographic techniques, 2004, pp. 523–540.
[10] Ahmed. T. S. Al-Obaidi, H. S. Abdullah, and Z. Othman., “Meerkat clan algorithm: A new swarm intelligence algorithm,” Indones. J. Electr. Eng. Comput. Sci., vol. 10, no. 1, pp. 354–360, 2018.
[11] G. Panchal and D. Samanta, “Comparable features and same cryptography key generation using biometric fingerprint image,” in 2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), 2016, pp. 691–695.
[12] G. Panchal and D. Samanta, “A novel approach to fingerprint biometric-based cryptographic key generation and its applications to storage security,” Comput. Electr. Eng., vol. 69, pp. 461–478, 2018.
[13] G. Panchal and D. Samanta, “Directional area based minutiae selection and cryptographic key generation using biometric fingerprint,” in Proceedings of the First International Conference on Computational Intelligence and Informatics, 2017, pp. 491–499.
[14] S. Barman, D. Samanta, and S. Chattopadhyay, “Fingerprint-based crypto-biometric system for network security,” EURASIP J. Inf. Secur., vol. 2015, no. 1, p. 3, 2015.
[15] S. Mishra and S. Bali, “Public key cryptography using genetic algorithm,” Int. J. Recent Technol. Eng., vol. 2, no. 2, pp. 150–154, 2013.
[16] S. Jhajharia, S. Mishra, and S. Bali, “Public key cryptography using particle swarm optimization and genetic algorithms,” Int. J. Adv. Res. Comput. Sci. Softw. Eng., vol. 3, no. 6, pp. 832–839, 2013.
[17] F. S. Abu-Mouti and M. E. El-Hawary, “Overview of artificial bee colony (ABC) algorithm and its applications,” in 2012 IEEE International Systems Conference SysCon 2012, 2012, pp. 1–6.
[18] M. Gheni, “An Approch to Identify and classify Iraqi Papers currency”. a PhD. Thesis, Department of computer Science, University of Technology, 2019.