Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Woo, Jiheon | - |
dc.contributor.author | Yoo, Chanhee | - |
dc.contributor.author | Kim, Young-Sik | - |
dc.contributor.author | Cassuto, Yuval | - |
dc.contributor.author | Kim, Yongjune | - |
dc.date.accessioned | 2023-10-23T15:10:19Z | - |
dc.date.available | 2023-10-23T15:10:19Z | - |
dc.date.created | 2023-06-16 | - |
dc.date.issued | 2023-05 | - |
dc.identifier.issn | 1556-6013 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/46533 | - |
dc.description.abstract | The min-entropy is a widely used metric to quantify the randomness of generated random numbers, which measures the difficulty of guessing the most likely output. It is difficult to accurately estimate the min-entropy of a non-independent and identically distributed (non-IID) source. Hence, NIST Special Publication (SP) 800-90B adopts ten different min-entropy estimators and then conservatively selects the minimum value among these ten min-entropy estimates. Among these estimators, the longest repeated substring (LRS) estimator estimates the collision entropy instead of the min-entropy by counting the number of repeated substrings. Since the collision entropy is an upper bound on the min-entropy, the LRS estimator inherently provides overestimated outputs. In this paper, we propose two techniques to estimate the min-entropy of a non-IID source accurately. The first technique resolves the overestimation problem by translating the collision entropy into the min-entropy. Next, we generalize the LRS estimator by adopting the general Rényi entropy instead of the collision entropy (i.e., Rényi entropy of order two). We show that adopting a higher order can reduce the variance of min-entropy estimates. By integrating these techniques, we propose a generalized LRS estimator that effectively resolves the overestimation problem and provides stable min-entropy estimates. Theoretical analysis and empirical results support that the proposed generalized LRS estimator improves the estimation accuracy significantly, which makes it an appealing alternative to the LRS estimator. © IEEE. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Generalized LRS Estimator for Min-entropy Estimation | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/TIFS.2023.3280745 | - |
dc.identifier.scopusid | 2-s2.0-85161084413 | - |
dc.identifier.bibliographicCitation | IEEE Transactions on Information Forensics and Security, v.18, pp.3305 - 3317 | - |
dc.description.isOpenAccess | FALSE | - |
dc.subject.keywordAuthor | Entropy estimation | - |
dc.subject.keywordAuthor | min-entropy | - |
dc.subject.keywordAuthor | collision entropy | - |
dc.subject.keywordAuthor | Rényi entropy | - |
dc.subject.keywordAuthor | NIST SP 800-90B | - |
dc.subject.keywordAuthor | random number generator | - |
dc.subject.keywordPlus | PROBABILITY | - |
dc.citation.endPage | 3317 | - |
dc.citation.startPage | 3305 | - |
dc.citation.title | IEEE Transactions on Information Forensics and Security | - |
dc.citation.volume | 18 | - |
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