Design of Testable Random Bit Generators

  • Marco Bucci
  • Raimondo Luzzi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3659)


In this paper, the evaluation of random bit generators for security applications is discussed and the concept of stateless generator is introduced. It is shown how, for the proposed class of generators, the verification of a minimum entropy limit can be performed directly on the post-processed random numbers thus not requiring a good statistic quality for the noise source itself, provided that a sufficient compression is adopted in the post-processing unit. Assuming that the noise source is stateless, a straightforward entropy estimator to drive an adaptive compression algorithm is proposed. Examples of stateless sources are also discussed.

Finally, an attack scenario against a noise source is defined and an effective approach to the attack detection is presented. The entropy estimator and the attack detection together guarantee the unpredictability of the generated random numbers.


Random bit source random numbers entropy ring oscillators jitter 


  1. 1.
    Menezes, A.J., Oorschot, P.C., Vanstone, S.A.: Handbook of Applied Cryptography. CRC Press, Boca Raton (2001)Google Scholar
  2. 2.
    Schindler, W.: Efficient Online Tests for True Random Number Generators. In: Koç, Ç.K., Naccache, D., Paar, C. (eds.) CHES 2001. LNCS, vol. 2162, pp. 103–117. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  3. 3.
    Killmann, W., Schindler, W.: AIS 31: Functionality classes and evaluation methodology for true (physical) random number generators. version 3.1, Bundesamt fur Sicherheit in der Informationstechnik (BSI), Bonn (2001)Google Scholar
  4. 4.
    Stojanovski, T., Kocarev, L.: Chaos-Based Random Number Generators - Part I: Analysis. IEEE Trans. Circuits and Systems I 48(3), 281–288 (2001)MATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Stojanovski, T., Pihl, J., Kocarev, L.: Chaos-Based Random Number Generators - Part II: Practical Realization. IEEE Trans. Circuits and Systems I 48(3), 382–385 (2001)MATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Bagini, V., Bucci, M.: A Design of Reliable True Random Number Generator for Cryptographic Applications. In: Koç, Ç.K., Paar, C. (eds.) CHES 1999. LNCS, vol. 1717, pp. 204–218. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  7. 7.
    Trichina, E., Bucci, M., De Seta, D., Luzzi, R.: Supplementary Cryptographic Hardware for Smart Cards. IEEE Micro 21(6), 26–35 (2001)CrossRefGoogle Scholar
  8. 8.
    Dichtl, M., Janssen, N.: A High Quality Physical Random Number Generator. In: Proc. Sophia Antipolis Forum Microelectronics (SAME 2000), pp. 48–53 (2000)Google Scholar
  9. 9.
    Jun, B., Kocher, P.: The Intel Random Number Generator. Cryptographic Research Inc., white paper prepared for Intel Corp. (April 1999),
  10. 10.
    Petrie, C.S., Connelly, J.A.: Modeling and Simulation of Oscillator-Based Random Number Generators. In: Proc. IEEE Int’l Symp. Circuits and Systems (ISCAS 1996), vol. 4, pp. 324–327 (1996)Google Scholar
  11. 11.
    Bucci, M., Germani, L., Luzzi, R., Trifiletti, A., Varanonuovo, M.: A High-Speed Oscillator-Based Truly Random Number Source for Cryptographic Applications. IEEE Trans. Computers 52(4), 403–409 (2003)CrossRefGoogle Scholar
  12. 12.
    Bock, H., Bucci, M., Luzzi, R.: An Offset-Compensated Oscillator-based Random Bit Source for Security Applications. In: Joye, M., Quisquater, J.-J. (eds.) CHES 2004. LNCS, vol. 3156, pp. 268–281. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  13. 13.
    Mandal, S., Banerjee, S.: An Integrated CMOS Chaos Generator. In: Proc. 1st Indian National Conf. Nonlinear Systems & Dynamics (NCNSD 2003), pp. 313–316 (December 2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Marco Bucci
    • 1
  • Raimondo Luzzi
    • 1
  1. 1.Infineon Technologies Austria AGGrazAUSTRIA

Personalised recommendations