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
-
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},
url = {https://eprint.iacr.org/2016/325}
}
