Exploiting Crosstalk Effects in FPGAs for Generating True Random Numbers

  • Octavian Creţ
  • Radu Tudoran
  • Alin Suciu
  • Tamas Györfi
Part of the Communications in Computer and Information Science book series (CCIS, volume 130)


This paper presents a new method for implementing TRNGs in FPGA devices, which relies on filling a region or the whole FPGA chip close to its maximal capacity and exploiting the interconnection network as intensely as possible. This way, there are strong chances for the design to exhibit a nondeterministic behavior. Our first design is a computationally intensive core that generates 64-bit numbers, accumulated into a fixed-point accumulator. The bits that exhibit the maximal entropy are then post-processed using the XOR-based bias reduction method. We prove that the resulting TRNG provides high quality random numbers. An explanation of the underlying phenomenon is proposed, based on electromagnetic interferences inside the chip and crosstalk effects. A systematic method for developing TRNG designs based on this approach is proposed and an improved TRNG architecture is then presented.


True random number generators FPGA Electrostatic and magnetic interferences Crosstalk effects 


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  1. 1.
    Marsaglia, G.: DIEHARD: Battery of Tests of Randomness (1996),
  2. 2.
    Rukhin, A., Soto, J., Nechvatal, J., Smid, M., Barker, E., Leigh, S., Levenson, M., Vangel, M., Banks, D., Heckert, A., Dray, J., Vo, S.: A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications. NIST Special Publication 800-22 (with revisions dated May 15, 2001) (2001),
  3. 3.
    L’Ecuyer, P., Simard, R.: TestU01: A C library for empirical testing of random number generators. ACM Transactions on Mathematical Software 33(4), 22 (2007)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Drutarovsky, M., Galajda, P.: A robust chaos-based true random number generator embedded in reconfigurable switched-capacitor hardware. Radioelektronika (April 2007)Google Scholar
  5. 5.
    Gentle, E.J.: Random Number Generation and Monte Carlo Methods. Springer, Heidelberg (2004)zbMATHGoogle Scholar
  6. 6.
    Kohlbrenner, P., Gaj, K.: An Embedded True Random Number Generator for FPGAs. In: Proceedings of the ACM/SIGDA 12th International Symposium on Field Programmable Gate Arrays, Monterey, California, pp. 71–78 (2004)Google Scholar
  7. 7.
    Schellekens, D., Preneel, B., Verbauwhede, I.: FPGA Vendor Agnostic True Random Number Generator. In: Proceedings of the International Conference on Field Programmable Logic and Applications, Madrid, pp. 1–6 (2006)Google Scholar
  8. 8.
    Jun, B., Kocher, P.: The Intel Random Number Generator. Cryptography Research, Inc. White Paper prepared for Intel Corporation (1999),
  9. 9.
    Drutarovsky, M., Galajda, P.: Chaos-based true random number generator embedded in a mixed-signal reconfigurable hardware. Journal of Electrical Engineering 57(4), 218–225 (2006)Google Scholar
  10. 10.
  11. 11.
    Creţ, O., Trestian, I., De Dinechin, F., Darabant, L., Tudoran, R., Văcariu, L.: Accelerating The Computation of The Physical Parameters Involved in Transcranial Magnetic Stimulation Using FPGA Devices. Romanian Journal of Information, Science and Technology 10(4), 361–379 (2008)Google Scholar
  12. 12.
    De Dinechin, F., Detrey, J., Creţ, O., Tudoran, R.: When FPGAs are better at floating-point than microprocessors. In: Sixteenth ACM/SIGDA International Symposium on Field Programmable Gate Arrays, Monterey, California (2008)Google Scholar
  13. 13.
    Fischer, V., Drutarovsky, M.: True random number generator embedded in reconfigurable hardware. In: Kaliski Jr., B.S., Koç, Ç.K., Paar, C. (eds.) CHES 2002. LNCS, vol. 2523, pp. 415–430. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  14. 14.
    Thompson, A.: An evolved circuit, intrinsic in silicon, entwined with physics. In: Higuchi, T., Iwata, M., Weixin, L. (eds.) ICES 1996. LNCS, vol. 1259, pp. 390–405. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  15. 15.
    Thompson, A., Layzell, P.: Analysis of Unconventional Evolved Electronics. Communications of the ACM 42(4), 71–79 (1999)CrossRefGoogle Scholar
  16. 16.
    The CryptoRand project (2010),

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Octavian Creţ
    • 1
  • Radu Tudoran
    • 1
  • Alin Suciu
    • 1
  • Tamas Györfi
    • 1
  1. 1.Technical University of Cluj-NapocaCluj-NapocaRomania

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