In the current information age, asymmetrical cryptography is widely used to protect information and financial transactions such as cryptocurrencies. The loss of private keys can have catastrophic consequences; therefore, effective MFA schemes are needed. In this paper, we focus on generating ephemeral keys to protect private keys. We propose a novel bit-truncation method in which the most significant bits (MSBs) of response values derived from facial features in a template-less biometric scheme are removed, significantly improving both accuracy and security. A statistical analysis is presented to optimize an MFA comprising at least three factors: template-less biometrics, an SRAM PUF-based token, and passwords. The results show a reduction in both false-reject and false-acceptance rates, and the generation of error-free ephemeral keys.
@article{arxiv.2603.05978,
title = {Statistical Analysis and Optimization of the MFA Protecting Private Keys},
author = {Mahafujul Alam and Julie B. Heynssens and Bertrand Francis Cambou},
journal= {arXiv preprint arXiv:2603.05978},
year = {2026}
}