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Mobile Authentication Using Iris Biometrics

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 294))

Abstract

In today’s fast moving world, mobile phones have become one of the basic needs and mobile security is of a major concern. Mobile security is needed to assure a secured method for mobile transactions and to preserve data integrity and confidentiality. The present method of security involves password authentication. However this method is highly vulnerable to spoof attacks. Biometrics based authentication is a popular method of providing security. This paper proposes a novel method to provide security in mobile phones using biometrics. Among all the biometric modalities, Iris is proven to be one of the best traits and most suitable for authenticating mobile phone users. The challenging issue in the iris based authentication is localizing iris, the Region of Interest (ROI) and extracting features for real-time images due to varying illumination conditions. The proposed scheme adapts Sobel operator in color space and Contour method to accurately detect and segment the iris from eye image. The feature extraction is by Discrete Wavelet Transform (DWT), for accurate classification, simple k-Nearest Neighbor (k-NN) is taken and based on the percentage of match the authentication is done. The proposed algorithm is using JavaCV (Java + OpenCV), tested in Android 2.2 platform and implemented in Samsung I9003 Galaxy S with Android 2.2 OS, processing speed of 1 GHz and Internal Memory of 4GB.

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References

  1. Wildes, R.P.: Iris Recognition: An Emerging Biometric Technology. Proceedings of the IEEE 85, 1348–1363 (1997)

    Article  Google Scholar 

  2. Laine, A., Fan, J.: Texture Classification by Wavelet Packet Signatures. IEEE Transaction Pattern Analysis Machine Intelligence 15, 1186–1191 (1993)

    Article  Google Scholar 

  3. Prabhakar, S., Pankanti, S., Jain, A.K.: Biometric Recognition: Security and Privacy Concerns. IEEE Security & Privacy, 33–42 (2003)

    Google Scholar 

  4. Masek, L.: Recognition of Human Iris Patterns for Biometric Identification. BE Dissertation, University of Western Australia, vol. 26 (2003)

    Google Scholar 

  5. Yang, S., Verbauwhede, I.: Secure Iris Verification. In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2007), Honolulu, Hawaii, USA, April 15-20, vol. 02, pp. 133–136 (2007)

    Google Scholar 

  6. Ma, L., Wang, Y., Tan, T.: Iris recognition using circular symmetric filters. In: In:Proc. of IAPR International Conference on Pattern Recognition (ICPR), National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, vol. 02, pp. 414–417 (December 2002)

    Google Scholar 

  7. Bodade, R., Talbar, M., Sanjay, N.: Shift Invariant Iris Feature Extraction Using Rotated Complex Wavelet and Complex Wavelet for Iris Recognition System. In: Seventh International Conference on Advances in Pattern Recognition (ICAPR), pp. 449–452 (2009)

    Google Scholar 

  8. Naresh Babu, N.T., Vaidehi, V.: Fuzzy Based IRIS Recognition System (FIRS) For Person Identification. In: IEEE, International Conference on Recent Trends in Information Technology (ICRTIT 2011) (2011) 978-1-4577-0590-8/11

    Google Scholar 

  9. Zhu, Y., Tan, T.: Yusag: Biometric Personal Identification based on Iris Patterns. In: 15th Internal Configuration Pattern Recognition, vol. 2(3), pp. 801–804 (2004)

    Google Scholar 

  10. Chitaliya, N.G., Trivedi, A.I.: Feature Extraction using Wavelet-PCA and Neural network for application of Object Classification & Face Recognition. In: International Conference on Computer Engineering and Applications (ICCEA 2010), pp. 510–514. IEEE Computer Society (2010)

    Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Gargi, M., Jasmine Sylvia Rani, J., Ramiah, M., Naresh Babu, N.T., Annis Fathima, A., Vaidehi, V. (2012). Mobile Authentication Using Iris Biometrics. In: Benlamri, R. (eds) Networked Digital Technologies. NDT 2012. Communications in Computer and Information Science, vol 294. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30567-2_28

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  • DOI: https://doi.org/10.1007/978-3-642-30567-2_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30566-5

  • Online ISBN: 978-3-642-30567-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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