Optimizing Linear Correctors: A Tight Output Min-Entropy Bound and Selection Technique
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2023
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| _version_ | 1866911930071908352 |
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| author | Grujić, Miloš Verbauwhede, Ingrid |
| author_facet | Grujić, Miloš Verbauwhede, Ingrid |
| contents | Post-processing of the raw bits produced by a true random number generator (TRNG) is always necessary when the entropy per bit is insufficient for security applications. In this paper, we derive a tight bound on the output min-entropy of the algorithmic post-processing module based on linear codes, known as linear correctors. Our bound is based on the codes' weight distributions, and we prove that it holds even for the real-world noise sources that produce independent but not identically distributed bits. Additionally, we present a method for identifying the optimal linear corrector for a given input min-entropy rate that maximizes the throughput of the post-processed bits while simultaneously achieving the needed security level. Our findings show that for an output min-entropy rate of $0.999$, the extraction efficiency of the linear correctors with the new bound can be up to $130.56\%$ higher when compared to the old bound, with an average improvement of $41.2\%$ over the entire input min-entropy range. On the other hand, the required min-entropy of the raw bits for the individual correctors can be reduced by up to $61.62\%$. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2304_05306 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Optimizing Linear Correctors: A Tight Output Min-Entropy Bound and Selection Technique Grujić, Miloš Verbauwhede, Ingrid Cryptography and Security Post-processing of the raw bits produced by a true random number generator (TRNG) is always necessary when the entropy per bit is insufficient for security applications. In this paper, we derive a tight bound on the output min-entropy of the algorithmic post-processing module based on linear codes, known as linear correctors. Our bound is based on the codes' weight distributions, and we prove that it holds even for the real-world noise sources that produce independent but not identically distributed bits. Additionally, we present a method for identifying the optimal linear corrector for a given input min-entropy rate that maximizes the throughput of the post-processed bits while simultaneously achieving the needed security level. Our findings show that for an output min-entropy rate of $0.999$, the extraction efficiency of the linear correctors with the new bound can be up to $130.56\%$ higher when compared to the old bound, with an average improvement of $41.2\%$ over the entire input min-entropy range. On the other hand, the required min-entropy of the raw bits for the individual correctors can be reduced by up to $61.62\%$. |
| title | Optimizing Linear Correctors: A Tight Output Min-Entropy Bound and Selection Technique |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2304.05306 |