Advertisement

Evaluation of a PUF Device Authentication Scheme on a Discrete 0.13um SRAM

  • Patrick Koeberl
  • Jiangtao Li
  • Roel Maes
  • Anand Rajan
  • Claire Vishik
  • Marcin Wójcik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7222)

Abstract

The contamination of electronic component supply chains by counterfeit hardware devices is a serious and growing risk in today’s globalized marketplace. Current best practice for detecting counterfeit semiconductors includes visual checking, electrical testing, and reliability testing, all of which require significant investments in expertise, equipment, and time. In TRUST’11, Koeberl, Li, Rajan, Vishik, and Wu proposed a new device authentication scheme using SRAM Physically Unclonable Functions (PUFs) for semiconductor anti-counterfeiting. Their authentication scheme is simple, low cost, and practical. However, the method and corresponding parameters of their scheme are based on a theoretical SRAM PUF model without support from real experimental data. In this paper, we evaluate a real SRAM PUF on a discrete 0.13um SRAM, and use the PUF result to evaluate this device authentication scheme and show that this scheme indeed works well. We identify several gaps between the theoretical model and the experimental SRAM PUF result, and adjust the parameters of the scheme accordingly. In addition, we provide a new post-processing function that results in a smaller false rejection rate and false acceptance rate.

Keywords

physically unclonable functions device authentication hardware security anti-counterfeiting implementation evaluation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Armknecht, F., Maes, R., Sadeghi, A.-R., Sunar, B., Tuyls, P.: PUF-PRFs: A new tamper-resilient cryptographic primitive. In: Advances in Cryptology – EUROCRYPT 2009 Poster Session, pp. 96–102 (2000)Google Scholar
  2. 2.
    Azizi, N., Moshovos, A., Najm, F.N.: Low-leakage asymmetric-cell sram. In: Proceedings of the 2002 International Symposium on Low Power Electronics and Design, ISLPED 2002, pp. 48–51. ACM, New York (2002)CrossRefGoogle Scholar
  3. 3.
    Bulens, P., Standaert, F.-X., Quisquater, J.-J.: How to strongly link data and its medium: the paper case. IET Information Security 4(3), 125–136 (2010)CrossRefGoogle Scholar
  4. 4.
    Gassend, B., Clarke, D., van Dijk, M., Devadas, S.: Silicon physical random functions. In: ACM Conference on Computer and Communications Security, pp. 148–160. ACM Press, New York (2002)Google Scholar
  5. 5.
    Guajardo, J., Kumar, S.S., Schrijen, G.-J., Tuyls, P.: FPGA Intrinsic PUFs and Their Use for IP Protection. In: Paillier, P., Verbauwhede, I. (eds.) CHES 2007. LNCS, vol. 4727, pp. 63–80. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  6. 6.
    Holcomb, D.E., Burleson, W.P., Fu, K.: Initial SRAM state as a fingerprint and source of true random numbers for RFID tags. In: Conference on RFID Security 2007, Malaga, Spain, July 11-13 (2007)Google Scholar
  7. 7.
    Kim, J.-J., Rao, R., Kim, K.: Technology-circuit co-design of asymmetric sram cells for read stability improvement. In: 2010 IEEE Custom Integrated Circuits Conference (CICC), pp. 1–4 (September 2010)Google Scholar
  8. 8.
    Koeberl, P., Li, J., Rajan, A., Vishik, C., Wu, W.: A Practical Device Authentication Scheme Using SRAM PUFs. In: McCune, J.M., Balacheff, B., Perrig, A., Sadeghi, A.-R., Sasse, A., Beres, Y. (eds.) Trust 2011. LNCS, vol. 6740, pp. 63–77. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  9. 9.
    Maes, R., Tuyls, P., Verbauwhede, I.: Intrinsic pufs from flip-flops on reconfigurable devices. In: 3rd Benelux Workshop on Information and System Security (WISSec 2008), Eindhoven, NL, p. 17 (2008)Google Scholar
  10. 10.
    Maes, R., Tuyls, P., Verbauwhede, I.: Soft decision helper data algorithm for sram pufs. In: Proceedings of the 2009 IEEE International Conference on Symposium on Information Theory, ISIT 2009, vol. 3, pp. 2101–2105. IEEE Press, Piscataway (2009)Google Scholar
  11. 11.
    Menezes, A., van Oorschot, P.C., Vanstone, S.A.: Handbook of Applied Cryptography. CRC Press (1996)Google Scholar
  12. 12.
    U. S. G. A. Office. Defense supplier base: Dod should leverage ongoing initiatives in developing its program to mitigate risk of counterfeit parts. GAO-10-389 (March 2010)Google Scholar
  13. 13.
    Pappu, R.S.: Physical one-way functions. PhD thesis, Massachusetts Institute of Technology (March 2001)Google Scholar
  14. 14.
    SEMI T20-1109. Specification for authentication of semiconductors and related products (2009), http://www.semi.org/
  15. 15.
    Suh, G.E., Devadas, S.: Physical unclonable functions for device authentication and secret key generation. In: Design Automation Conference, pp. 9–14. ACM Press, New York (2007)Google Scholar
  16. 16.
    Trusted Computing Group. TCG TPM specification 1.2 (2003), http://www.trustedcomputinggroup.org
  17. 17.
    von Neumann, J.: Various techniques used in connection with random digits. In: Householder, A.S., et al. (eds.) The Monte Carlo Method. National Bureau of Standards, Applied Mathematics Series, vol. 12, pp. 36–38 (1951)Google Scholar
  18. 18.
    Xilinx Inc. ML501 Evaluation Platform - User Guide, UG226 (v1.4), August 24 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Patrick Koeberl
    • 1
  • Jiangtao Li
    • 1
  • Roel Maes
    • 2
  • Anand Rajan
    • 1
  • Claire Vishik
    • 1
  • Marcin Wójcik
    • 3
  1. 1.Intel CorporationIreland
  2. 2.Catholic University of LeuvenBelgium
  3. 3.University of BristolUK

Personalised recommendations