Statistical Analysis and Optimization of the MFA Protecting Private Keys
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| _version_ | 1866908870053462016 |
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| author | Alam, Mahafujul Heynssens, Julie B. Cambou, Bertrand Francis |
| author_facet | Alam, Mahafujul Heynssens, Julie B. Cambou, Bertrand Francis |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_05978 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Statistical Analysis and Optimization of the MFA Protecting Private Keys Alam, Mahafujul Heynssens, Julie B. Cambou, Bertrand Francis Cryptography and Security E.3; C.2; G.3 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. |
| title | Statistical Analysis and Optimization of the MFA Protecting Private Keys |
| topic | Cryptography and Security E.3; C.2; G.3 |
| url | https://arxiv.org/abs/2603.05978 |