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Journal of Hardware and Systems Security

, Volume 3, Issue 1, pp 78–93 | Cite as

Variable-Length Bit Mapping and Error-Correcting Codes for Higher-Order Alphabet PUFs—Extended Version

  • Vincent ImmlerEmail author
  • Matthias Hiller
  • Qinzhi Liu
  • Andreas Lenz
  • Antonia Wachter-Zeh
Article
  • 60 Downloads

Abstract

Device-specific physical characteristics provide the foundation for physical unclonable functions (PUFs), a hardware primitive for secure storage of cryptographic keys. Thus far, they have been implemented by either directly evaluating a binary output or by mapping symbols from a higher-order alphabet to a fixed-length bit sequence. However, when combined with equidistant quantization, this causes significant bias in the derived secret which is a security issue. To overcome this limitation, we propose a variable-length bit mapping that reflects the properties of a Gray code in a different metric, namely the Levenshtein metric instead of the classical Hamming metric. Subsequent error correction is therefore based on a custom insertion/deletion error-correcting code (ECC). This new approach effectively counteracts the bias in the derived key already at the input side of the ECC. We present the concept for our scheme and demonstrate its feasibility based on an empirical PUF distribution. As a result, we increase the effective output bit length of the secret by over 40% compared to state-of-the-art approaches. In addition to that, we investigate different segmentation approaches which is important due to the variable length of the considered values. Practical implementation results demonstrate that the proposed scheme requires only a fraction of the execution time compared to Bose-Chaudhuri-Hocquenghem (BCH) codes. This opens up a new direction of ECCs for PUFs that output responses with symbols of a higher-order alphabet.

Keywords

Physical unclonable functions Fuzzy extractor Secrecy leakage Coding theory Quantization Varshamov-Tenengolts (VT) code 

Notes

Acknowledgements

Many thanks to Aysun Önalan for preparing the numbers of the RS-based fuzzy commitment scheme.

Funding Information

The authors from Fraunhofer AISEC have been supported by the Fraunhofer Internal Programs under Grant no. MAVO 828 432. A. Lenz and A. Wachter-Zeh have been supported by the Technical University of Munich–Institute for Advanced Study, funded by the German Excellence Initiative and European Union Seventh Framework Programme under Grant Agreement No. 291763.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Fraunhofer Institute AISECGarching near MunichGermany
  2. 2.RWTH Aachen UniversityAachenGermany
  3. 3.Institute for Communications EngineeringTechnical University of Munich (TUM)MunichGermany

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