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Multi-modal Techniques for Identity Theft Prevention

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3597))

Abstract

The rapid growth of the Internet has caused a large number of social problems including invasion of privacy and violation of personal identity. Currently, it is an emerging trend to verify personal identity based on hybrid methods (for example, by combining the existing off-line and on-line verification methods) using the Internet in the legacy applications. As a result, many security problems of the Internet is now becoming the practical impacts on our social applications. In this paper, we study multi-modal techniques for preventing identity theft in the social applications from the practical perspectives. A digital signature techniques and multi-modal biometrics are exploited in our scheme without requiring users to hold additional hardware devices.

This research was supported by the MIC (Ministry of Information and Communication), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute of Information Technology Assessment).

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References

  1. Belhumueur, P., Hespanha, J., Krieman, D.: Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 711–720 (1997)

    Google Scholar 

  2. Daon Inc., Biometric Authentication & Digital Signatures for the Pharmaceutical Industry, White paper available at http://www.daon.com/downloads/publications/esignature.pdf

  3. Guillou, L., Quisquater, J.: A practical zero-knowledge protocol fitted to security microprocessor minimizing both transmission and memory. In: Günther, C.G. (ed.) EUROCRYPT 1988. LNCS, vol. 330, pp. 123–128. Springer, Heidelberg (1988)

    Google Scholar 

  4. Kwon, T.: Practical digital signature generation using biometrics. In: Laganá, A., Gavrilova, M.L., Kumar, V., Mun, Y., Tan, C.J.K., Gervasi, O. (eds.) ICCSA 2004. LNCS, vol. 3043, pp. 728–737. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  5. Kwon, T., Moon, H.: Multi-modal biometrics with PKI technologies for border control applications. In: Kantor, P., Muresan, G., Roberts, F., Zeng, D.D., Wang, F.-Y., Chen, H., Merkle, R.C. (eds.) ISI 2005. LNCS, vol. 3495, pp. 99–114. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  6. Liu, C., Wechsler, H.: Gabor Feature Based Classification Using the Enhanced Fisher Linear Discriminant Model for Face Recognition. IEEE Transactions on Image Processing, 467–476 (2002)

    Google Scholar 

  7. Menezes, A., van Oorschot, P., Vanstone, S.: Handbook of Applied Cryptography, pp. 287–291, 312–315. CRC Press, Boca Raton (1997)

    Google Scholar 

  8. Messer, K., Matas, J., Kittler, J., Luettin, J., Maitre, G.: XM2VTSDB: The Extended M2VTS Database. In: Proc. of International Conference on Audio- and Video-Based Person Authentication, pp. 72–77 (1999)

    Google Scholar 

  9. Palmer, R.: The Bar Code Book, 3rd edn. Helmers Publishing, Peterborough (1995)

    Google Scholar 

  10. Rivest, R., Shamir, A., Adleman, L.: A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM 21, 120–126 (1978)

    Article  MATH  MathSciNet  Google Scholar 

  11. Phillips, P., Moon, H., Rizvi, S., Rauss, P.: The FERET Evaluation Methodology for Face-Recognition Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1090–1104 (2000)

    Google Scholar 

  12. Soutar, C., Roberge, D., Stoianov, A., Golroy, R., Vijaya Kumar, B.: Biometric Encryption. ICSA Guide to Cryptography. McGraw-Hill, New York (1999), also available at http://www.bioscrypt.com/assets/Biometric_Encryption.pdf

  13. Turk, M., Pentland, A.: Eigenfaces for recognition. Journal of Cognitive Neuroscience 3(1), 71–86 (1991)

    Article  Google Scholar 

  14. Yang, J., Zhang, D., Frangi, A., Yang, J.: Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 131–137 (2004)

    Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Kwon, T., Moon, H. (2005). Multi-modal Techniques for Identity Theft Prevention. In: Shimojo, S., Ichii, S., Ling, TW., Song, KH. (eds) Web and Communication Technologies and Internet-Related Social Issues - HSI 2005. HSI 2005. Lecture Notes in Computer Science, vol 3597. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527725_30

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  • DOI: https://doi.org/10.1007/11527725_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27830-6

  • Online ISBN: 978-3-540-31808-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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