Wireless Personal Communications

, Volume 97, Issue 3, pp 4729–4745 | Cite as

An Efficient Biometric Based Remote User Authentication Technique for Multi-server Environment

  • NehaEmail author
  • Kakali Chatterjee


With the increasing demand of remote user authentication process for accessing many Internet based applications, biometrics based authentication mechanisms are highly being adopted. But using biometrics for these authentication mechanisms the features need to be captured and database need to be stored somewhere. Storing such a huge amount of biometric data itself has many security and privacy issues. Like revoking compromised biometric template is impossible. So template security is very important here. But due to low repeatability of biometrics, it is a challenging task to ensure template security while achieving high recognition performance of valid user. Hence, here we have proposed a keystroke based multi-server authentication mechanism which uses bio-hash template security technique. The bio-hash transform a biometric trait in an invariant feature which helps to increase the recognition performance. A comparison of normal keystroke dynamics and bio-hashed keystroke dynamics authentication performance has been done here. The bio-hashed keystroke shows better ERR of 0.15% compared to plain keystroke with 0.231% ERR.


Bio-hashing Biometrics Keystroke dynamics Multi-server 


  1. 1.
    Lamport, L. (1981). Password authentication with insecure communication. Communications of the ACM, 24(11), 770–772.MathSciNetCrossRefGoogle Scholar
  2. 2.
    Chang, C. C., & Wu, T. C. (1991). Remote password authentication with smart cards. IEEE Proceedings E-Computers and Digital Techniques, 138(3), 165–168.CrossRefGoogle Scholar
  3. 3.
    Haller, N. M. (1994). The S/KEY one-time password system. In Symposium on Network and Distributed Systems Security.Google Scholar
  4. 4.
    Shiuh-Jeng, W., & Jin-Fu, C. (1996). Smart card based secure password authentication scheme. Computers & Security, 15(3), 231–237.CrossRefGoogle Scholar
  5. 5.
    Fan, C. I., Chan, Y. C., & Zhang, Z. K. (2005). Robust remote authentication scheme with smart cards. Computers & Security, 24(8), 619–628.CrossRefGoogle Scholar
  6. 6.
    Lee, S. W., Kim, H. S., & Yoo, K. Y. (2005). Efficient nonce-based remote user authentication scheme using smart cards. Applied Mathematics and Computation, 167(1), 355–361.MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Liu, J. Y., Zhou, A. M., & Gao, M. X. (2008). A new mutual authentication scheme based on nonce and smart cards. Computer Communications, 31(10), 2205–2209.CrossRefGoogle Scholar
  8. 8.
    Lee, J. K., Ryu, S. R., & Yoo, K. Y. (2002). Fingerprint-based remote user authentication scheme using smart cards. Electronics Letters, 38(12), 1.Google Scholar
  9. 9.
    Lin, C. H., & Lai, Y. Y. (2004). A flexible biometrics remote user authentication scheme. Computer Standards & Interfaces, 27(1), 19–23.CrossRefGoogle Scholar
  10. 10.
    Chang, C. C., & Lin, I. C. (2004). Remarks on fingerprint-based remote user authentication scheme using smart cards. ACM SIGOPS Operating Systems Review, 38(4), 91–96.CrossRefGoogle Scholar
  11. 11.
    Kim, H. S., Lee, S. W., & Yoo, K. Y. (2003). ID-based password authentication scheme using smart cards and fingerprints. ACM SIGOPS Operating Systems Review, 37(4), 32–41.CrossRefGoogle Scholar
  12. 12.
    Scott, M. (2004). Cryptanalysis of an ID-based password authentication scheme using smart cards and fingerprints. ACM SIGOPS Operating Systems Review, 38(2), 73–75.MathSciNetCrossRefGoogle Scholar
  13. 13.
    Uludag, U., Pankanti, S., Prabhakar, S., & Jain, A. K. (2004). Biometric cryptosystems: issues and challenges. In Proceedings of the IEEE 92, 6, pp. 948–960.Google Scholar
  14. 14.
    Bhargav-Spantzel, A., Squicciarini, A. C., Modi, S., Young, M., Bertino, E., & Elliott, S. J. (2007). Privacy preserving multi-factor authentication with biometrics. Journal of Computer Security, 15(5), 529–560.CrossRefGoogle Scholar
  15. 15.
    Khan, M. K., & Zhang, J. (2007). Improving the security of a flexible biometrics remote user authentication scheme. Computer Standards & Interfaces, 29(1), 82–85.CrossRefGoogle Scholar
  16. 16.
    Li, C. T., & Hwang, M. S. (2010). An efficient biometrics-based remote user authentication scheme using smart cards. Journal of Network and Ccomputer Applications, 33(1), 1–5.CrossRefGoogle Scholar
  17. 17.
    Li, X., Niu, J.-W., Ma, J., Wang, W.-D., & Liu, C.-L. (2011). Cryptanalysis and improvement of a biometrics-based remote user authentication scheme using smart cards. Journal of Network and Computer Applications, 34(1), 73–79.CrossRefGoogle Scholar
  18. 18.
    Das, A. K. (2011). Analysis and improvement on an efficient biometric-based remote user authentication scheme using smart cards. IET Information Security, 5(3), 145–151.CrossRefGoogle Scholar
  19. 19.
    Yoon, E.-J., & Yoo, K.-Y. (2013). Robust biometrics-based multi-server authentication with key agreement scheme for smart cards on elliptic curve cryptosystem. The Journal of Supercomputing, 63(1), 235–255.CrossRefGoogle Scholar
  20. 20.
    Li, X., Niu, J., Wang, Z., & Chen, C. (2014). Applying biometrics to design three factor remote user authentication scheme with key agreement. Security and Communication Networks, 7(10), 1488–1497.Google Scholar
  21. 21.
    He, D., & Wang, D. (2015). Robust biometrics-based authentication scheme for multiserver environment. IEEE Systems Journal, 9(3), 816–823.CrossRefGoogle Scholar
  22. 22.
    Kim, H., Jeon, W., Lee, K., Lee, Y., & Won, D. (2012). Cryptanalysis and improvement of a biometrics-based multi-server authentication with key agreement scheme. Computational Science and Its Applications ICCSA, 2012, 391–406.Google Scholar
  23. 23.
    Jain, A. K., Nandakumar, K., & Nagar, A. (2008). Biometric template security. EURASIP Journal on Advances in Signal Processing, 2008, 113.CrossRefGoogle Scholar
  24. 24.
    Faundez-Zanuy, M. (2004). On the vulnerability of biometric security systems. IEEE Aerospace and Electronic Systems Magazine, 19(6), 3–8.CrossRefGoogle Scholar
  25. 25.
    Matsumoto, T., Matsumoto, H., Yamada, K., & Hoshino, S. (2002). Impact of artificial gummy fingers on fingerprint systems. In Electronic Imaging 2002 (pp. 275–289), International Society for Optics and Photonics.Google Scholar
  26. 26.
    Jain, A., Bolle, R., & Pankanti, S. (Eds.). (1999). Biometrics: Personal identification in networked society (Vol. 479). Berlin: Springer.Google Scholar
  27. 27.
    Adler, A. (2004). Images can be regenerated from quantized biometric match score data. In Canadian conference on electrical and computer engineering, 2004 (pp. 469–472). IEEEGoogle Scholar
  28. 28.
    Ross, A., Shah, J., & Jain, A. K. (2007). From template to image: Reconstructing fingerprints from minutiae points. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(4), 544–560.CrossRefGoogle Scholar
  29. 29.
    Cappelli, R., Maio, D., Lumini, A., & Maltoni, D. (2007). Fingerprint image reconstruction from standard templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(9), 1489–1503.CrossRefGoogle Scholar
  30. 30.
    Prabhakar, S., Pankanti, S., & Jain, A. K. (2003). Biometric recognition: Security and privacy concerns. IEEE Security & Privacy, 99(2), 33–42.CrossRefGoogle Scholar
  31. 31.
    Lin, M. C., & Canny, J. F. (1991). A fast algorithm for incremental distance calculation. Proceedings of IEEE international conference on robotics and automation, 1991 (pp. 1008–1014).Google Scholar
  32. 32.
    De Maesschalck, R., Jouan-Rimbaud, D., & Massart, D. L. (2000). The mahalanobis distance. Chemometrics and Intelligent Laboratory Systems, 50(1), 1–18.CrossRefGoogle Scholar
  33. 33.
    Kretz, T., Bnisch, C., & Vortisch, P. (2010). Comparison of various methods for the calculation of the distance potential field. In Pedestrian and evacuation dynamics 2008 (pp. 335–346). Berlin, Heidelberg: Springer.Google Scholar
  34. 34.
    Zhong, Y., Deng, Y., & Jain, A. K. (2012). Keystroke dynamics for user authentication. In 2012 IEEE computer society conference on computer vision and pattern recognition workshops (CVPRW) (pp. 117–123).Google Scholar
  35. 35.
    Boneh, D. (2011). BlumBlumShub pseudorandom bit generator. Encyclopedia of cryptography and security (pp. 160–160). US: Springer.Google Scholar
  36. 36.
    Chen, J., Tian, C., Berger, T., & Hemami, S. S. (2006). Multiple description quantization via Gram Schmidt orthogonalization. IEEE Transactions on Information Theory, 52(12), 5197–5217.MathSciNetzbMATHCrossRefGoogle Scholar
  37. 37.
    Nanni, L., & Lumini, A. (2008). Random subspace for an improved biohashing for face authentication. Pattern Recognition Letters, 29(3), 295–300.zbMATHCrossRefGoogle Scholar

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© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringNational Institute of Technology PatnaPatnaIndia

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