Application of Minimum Entropy Estimation in Modal Analysis

2006 ◽  
Author(s):  
Minh Ta ◽  
Dayong Zhou ◽  
Victor DeBrunner
Keyword(s):  
Modal Analysis ◽  
Minimum Entropy ◽  
Entropy Estimation

scholarly journals Minimum-entropy estimation in semi-parametric models

2005 ◽  
Vol 85 (5) ◽  
pp. 937-949 ◽  
Author(s):  
Eric Wolsztynski ◽  
Eric Thierry ◽  
Luc Pronzato
Keyword(s):  
Parametric Models ◽  
Minimum Entropy ◽  
Entropy Estimation

scholarly journals Min-Entropy Estimation for Semiconductor Superlattice True Random Number Generators

2021 ◽  
Author(s):  
Jing Liu ◽  
Jianguo Xie ◽  
Lu Chao ◽  
Han Wu ◽  
Peng Ding ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Estimation Method ◽  
Random Model ◽  
Security Level ◽  
Minimum Entropy ◽  
Random Number Generators ◽  
Entropy Estimation ◽  
Average Value ◽  
Semiconductor Superlattice

Abstract Semiconductor superlattice true random number generator (SSL-TRNG) has an outstanding practical property to serve as high-throughput and high-security cryptographic applications. Security in random number generators is closely related to the min-entropy of the raw output because feeding cryptographic applications with insufficient entropy leads to poor security and vulnerability to malicious attacks. However, no research has focused on the minimum entropy estimation based on the random model for SSL-TRNG, which is a highly recommended method for evaluating the security of a specific TRNG structure. This paper proposes a min-entropy estimation method for the SSL-TRNG by extending the Markov stochastic model derived from the memory effects. By calculating the boundary of the transition matrix, the min-entropy result is that the average value of each sample (1 bit) is 0.2487. Moreover, we demonstrate that the estimator is accurate enough to adjust compression rate dynamically in post-processing to reach the required security level, estimating entropy on the fly rather than off-line.

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