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 | 2023-12-26T18:13:11Z | - |
dc.date.available | 2023-12-26T18:13:11Z | - |
dc.date.created | 2022-09-08 | - |
dc.date.issued | 2022-06-27 | - |
dc.identifier.isbn | 9781665421591 | - |
dc.identifier.issn | 2157-8095 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/46827 | - |
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 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 current-standard LRS estimator. © 2022 IEEE. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Generalized Longest Repeated Substring Min-Entropy Estimator | - |
dc.type | Conference Paper | - |
dc.identifier.doi | 10.1109/ISIT50566.2022.9834465 | - |
dc.identifier.scopusid | 2-s2.0-85136259156 | - |
dc.identifier.bibliographicCitation | 2022 IEEE International Symposium on Information Theory, ISIT 2022, pp.342 - 347 | - |
dc.identifier.url | https://www.isit2022.org/wp-content/uploads/2022/06/Booklet-of-Abstracts.pdf | - |
dc.citation.conferencePlace | FI | - |
dc.citation.conferencePlace | Espoo | - |
dc.citation.endPage | 347 | - |
dc.citation.startPage | 342 | - |
dc.citation.title | 2022 IEEE International Symposium on Information Theory, ISIT 2022 | - |
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