Paper 2016/325

Optimized quantization in Zero Leakage Helper Data Systems

Taras Stanko, Fitria Nur Andini, and Boris Skoric

Abstract

Helper Data Systems are a cryptographic primitive that allows for the reproducible extraction of secrets from noisy measurements. Redundancy data called Helper Data makes it possible to do error correction while leaking little or nothing ("Zero Leakage") about the extracted secret string. We study the case of non-discrete measurement outcomes. In this case a quantization step is required. Recently de Groot et al described a generic method to perform the quantization in a Zero Leakage manner. We extend their work and show how the quantization intervals should be set to maximize the amount of extracted secret key material when noise is taken into account.

Metadata
Available format(s)
PDF
Publication info
Preprint. MINOR revision.
Keywords
PUFbiometricsfuzzy extractor
Contact author(s)
b skoric @ tue nl
History
2016-03-25: received
Short URL
https://ia.cr/2016/325
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2016/325,
      author = {Taras Stanko and Fitria Nur Andini and Boris Skoric},
      title = {Optimized quantization in Zero Leakage Helper Data Systems},
      howpublished = {Cryptology ePrint Archive, Paper 2016/325},
      year = {2016},
      note = {\url{https://eprint.iacr.org/2016/325}},
      url = {https://eprint.iacr.org/2016/325}
}
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