Optimized Quantization in Zero Leakage Helper Data Systems
Taras Stanko, Fitria Nur Andini, Boris Škorić · IEEE Transactions on Information Forensics and Security · 2017
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 Grootet 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.