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An Improved Pseudo-random Generator Based on Discrete Log [chapter]

Rosario Gennaro
2000 Lecture Notes in Computer Science  
Under the assumption that solving the discrete logarithm problem modulo an n-bit prime p is hard even when the exponent is a small c-bit number, we construct a new and improved pseudo-random bit generator  ...  Using typical parameters, n = 1024 and c = 160, this yields roughly 860 pseudo-random bits per small exponentiations.  ...  [10] show that if one considers discrete-log modulo a composite then almost n/2 pseudo-random bits can be extracted per modular exponentiation.  ... 
doi:10.1007/3-540-44598-6_29 fatcat:lixhzkeihndqljlkmz3c6agjeq

An efficient discrete log pseudo random generator [chapter]

Sarvar Patel, Ganapathy S. Sundaram
1998 Lecture Notes in Computer Science  
This leads to a very efficient pseudo-random number generator which produces n -c bits per iteration.  ...  For example, when n = 1024 bits and c = 128 bits our pseudo-random number generator produces a tittle less than 900 bits per exponentiation.  ...  s of size to(log n) is hard to invert. 5 Pseudo Random Bit Generator In this section we provide the details of the new pseudo-random bit generator.  ... 
doi:10.1007/bfb0055737 fatcat:lyrdtbkcovcvfdut3sb2eocfti

Pseudo-random Number Generation on the IBM 4758 Secure Crypto Coprocessor [chapter]

Nick Howgrave-Graham, Joan Dyer, Rosario Gennaro
2001 Lecture Notes in Computer Science  
In this paper we explore pseudo-random number generation on the IBM 4758 Secure Crypto Coprocessor.  ...  In particular we compare several variants of Gennaro's provably secure generator, proposed at Crypto 2000, with more standard techniques based on the SHA-1 compression function.  ...  Conclusions The results show that the SHA-1 based pseudorandom number generation is still considerably faster than the one based on discrete logarithms.  ... 
doi:10.1007/3-540-44709-1_9 fatcat:ddehnwo5gzg5bdhkdfhswjrgoa

Optimal Discrete Uniform Generation from Coin Flips, and Applications [article]

Jérémie Lumbroso
2013 arXiv   pre-print
This article introduces an algorithm to draw random discrete uniform variables within a given range of size n from a source of random bits.  ...  I also provide a detailed analysis of the number of bits that are spent per variate, and offer some extensions and applications, in particular to the optimal random generation of permutations.  ...  and Axel Bacher for a discussion on Lehmer codes.  ... 
arXiv:1304.1916v1 fatcat:yydtdcmnyrg6phinmn5aa2lk6e

Privately Outsourcing Exponentiation to a Single Server: Cryptanalysis and Optimal Constructions [chapter]

Céline Chevalier, Fabien Laguillaumie, Damien Vergnaud
2016 Lecture Notes in Computer Science  
a constant number of (generic) group operations.  ...  We analyze the security of an efficient protocol for securely outsourcing multiexponentiations proposed at ESORICS 2014.  ...  When the base u is fixed, one can assume that C can use a pseudo-random power generator for u.  ... 
doi:10.1007/978-3-319-45744-4_13 fatcat:rfdnfaoo2vehreq4cb4bpbzb5i

Quality Prediction and Yield Improvement in Process Manufacturing Based on Data Analytics

Ji-hye Jun, Tai-Woo Chang, Sungbum Jun
2020 Processes  
Finally, in Step 3, we predict quality values based on the data obtained in Step 1 and Step 2 and calculate yield values with the use of the predicted value.  ...  However, it is more difficult to manage quality in continuous-flow manufacturing than in discrete manufacturing because partial defects can significantly affect the quality of an entire lot of final product  ...  In Step 1, loss data were generated by random forest-based pseudo labeler. In Step 2, feature data were predicted with RNN.  ... 
doi:10.3390/pr8091068 fatcat:3kkqgm2urrhozgwnjtd4aixgau

Speeding up discrete log and factoring based schemes via precomputations [chapter]

Victor Boyko, Marcus Peinado, Ramarathnam Venkatesan
1998 Lecture Notes in Computer Science  
Our constructions use random walks on Cayley (expander) graphs over Abelian groups. Our analysis involves non-linear versions of lattice problems.  ...  Our methods are novel in the sense that they identify and thoroughly exploit the randomness issues related to the instances generated in these public-key schemes.  ...  Kannan for discussions on methods for attacking hidden subset sum problems.  ... 
doi:10.1007/bfb0054129 fatcat:smvgjccijrht3j63u3ca7dcbxm

A statistical analysis of probabilistic counting algorithms [article]

Peter Clifford, Ioana A. Cosma
2010 arXiv   pre-print
We apply conventional statistical methods to compare probabilistic algorithms based on storing either selected order statistics, or random projections.  ...  We present a statistical analysis of probabilistic counting algorithms, focusing on two techniques that use pseudo-random variates to form low-dimensional data sketches.  ...  At time t, the data type i t is used as the seed of a random number generator to produce the first pseudo-random number h(i t ) uniformly distributed on (0,1). Write h(i t ) ∼ U(0, 1).  ... 
arXiv:0801.3552v3 fatcat:yhf6wknoofcphkwkxvqsw3eguq

Quasi-Random Sampling for Condensation [chapter]

Vasanth Philomin, Ramani Duraiswami, Larry Davis
2000 Lecture Notes in Computer Science  
The problem of tracking pedestrians from a moving car is a challenging one. The Condensation tracking algorithm is appealing for its generality and potential for real-time implementation.  ...  This paper presents an improved algorithm that addresses these problems by using a simplified motion model, and employing quasi-Monte Carlo techniques to efficiently sample the resulting tracking problem  ...  a log-log scale (base 2).  ... 
doi:10.1007/3-540-45053-x_9 fatcat:jmdctuc7ajbvrcdtuio7xizn34

A kinetic triangulation scheme for moving points in the plane

Haim Kaplan, Natan Rubin, Micha Sharir
2011 Computational geometry  
Thus, compared to the previous solution of Agarwal, Wang and Yu (2006) [4], we achieve a (slightly) improved bound on the number of discrete changes in the triangulation.  ...  Our triangulation scheme experiences an expected number of O (n 2 β s+2 (n) log 2 n) discrete changes, and handles them in a manner that satisfies all the standard requirements from a kinetic data structure  ...  Acknowledgements We thank the anonymous referees for valuable suggestions that helped us to improve the presentation.  ... 
doi:10.1016/j.comgeo.2010.11.001 fatcat:4bkhxtm6b5b5flanabhysxj5g4

Nearly One-Sided Tests and the Goldreich-Levin Predicate [chapter]

Gustav Hast
2003 Lecture Notes in Computer Science  
We provide an efficient reduction establishing improved security for the Goldreich-Levin hard-core bit against nearly one-sided tests.  ...  In particular, this applies to signature schemes that utilize a pseudo-random generator as a provider of randomness.  ...  Blum and Micali showed how to construct a pseudo-random bit generator (PRBG) whose security is based on the hardness of solving the discrete logarithm problem.  ... 
doi:10.1007/3-540-39200-9_12 fatcat:w55xlk3a4jcf5nhjtk4d5fwciu

Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model

Chandra R. Bhat
2001 Transportation Research Part B: Methodological  
We suggest and implement an alternative quasi-random maximum simulated likelihood method which uses cleverly crafted non-random but more uniformly distributed sequences in place of the pseudo-random points  ...  Keywords: Mixed multinomial logit model, maximum simulated likelihood estimation, pseudorandom sequences, quasi-random sequences, polynomial-based cubature, discrete choice analysis.  ...  The author would also like to thank Frank Koppelman and three referees for valuable comments on an earlier version of the paper.  ... 
doi:10.1016/s0191-2615(00)00014-x fatcat:svvjrjtvzfax3ainvpldrst6ma

Nearly One-Sided Tests and the Goldreich?Levin Predicate

Gustav Hast
2003 Journal of Cryptology  
We provide an efficient reduction establishing improved security for the Goldreich-Levin hard-core bit against nearly one-sided tests.  ...  In particular, this applies to signature schemes that utilize a pseudo-random generator as a provider of randomness.  ...  Blum and Micali showed how to construct a pseudo-random bit generator (PRBG) whose security is based on the hardness of solving the discrete logarithm problem.  ... 
doi:10.1007/s00145-003-0141-4 fatcat:tksbhy5hrjagtlntmeqbw2oy4e

Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences

Chandra R. Bhat
2003 Transportation Research Part B: Methodological  
Niederreiter, 1995 for a discussion of pseudo-random sequence generation).  ...  However, rather than using pseudo-random sequences for the discrete points, the quasi-Monte Carlo approach uses "cleverly" crafted non-random and more uniformly distributed  ...  Frank Koppelman, Kenneth Train, and an anonymous reviewer provided important suggestions for improvement on an earlier version of this paper.  ... 
doi:10.1016/s0191-2615(02)00090-5 fatcat:dy5lzxwqzzg3pf3wp4dbkeujou

Instantaneous Frequency Estimation Using Stochastic Calculus and Bootstrapping

A. Abutaleb
2005 EURASIP Journal on Advances in Signal Processing  
An approximate expression for the Cramér-Rao lower bound is derived. An example is given, and a comparison to existing methods is provided.  ...  Pseudo-maximum likelihood estimates are obtained through Girsanov theory and the Radon-Nikodym derivative.  ...  ( 1 ) 1 Discretize the form of the pseudo-log-likelihood function λ of (47) using the formulae in (80) and (81).(2) For a given γ, use (50) to find f .(3) For a given estimated f , use the simulation-based  ... 
doi:10.1155/asp.2005.1886 fatcat:7x6dptrnd5ehpbzpcafell2w4a
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