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Simulation Theorems via Pseudo-random Properties

Arkadev Chattopadhyay, Michal Koucký, Bruno Loff, Sagnik Mukhopadhyay
2019 Computational Complexity  
We generalize the deterministic simulation theorem of Raz & McKenzie (Combinatorica 19(3):403-435, 1999), to any gadget which satisfies a certain hitting property.  ...  We prove that inner product and gap-Hamming satisfy this property, and as a corollary, we obtain a deterministic simulation theorem for these gadgets, where the gadget's input size is logarithmic in the  ...  thms. via pseudo-random properties 619 have small discrepancy.  ... 
doi:10.1007/s00037-019-00190-7 fatcat:mjgfgs4bxzailncukfirhkgwny

A Bidirectional Generalized Synchronization Theorem -Based Chaotic Pseudorandom Number Generator

Han Shuangshuang, Min Lequan
2013 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
The confidence interval analysis showed the statistical properties of the randomness of the sequences generated via the CPNG and the RC4 algorithm do not have significant differences.  ...  Numerical simulation showed that two pair variables of the BGCSDS achieve generalized chaos synchronization via a transform H.  ...  The last procedure is to verify the randomness of binary sequence generated via the CPNG. All the simulations are implemented using Matlab 7.0.  ... 
doi:10.12928/telkomnika.v11i2.943 fatcat:rne2f6czdffuvdh4h46gtwfn2y

Black-Box Property of Cryptographic Hash Functions [chapter]

Michal Rjaško
2012 Lecture Notes in Computer Science  
If a hash function family is pseudo-random and has the black-box property then a randomly chosen hash function HK from the family is resistant to all non-trivial types of attack.  ...  We also show that the HMAC domain extension transform is Prf-BB preserving, i.e. if a compression function f is pseudo-random and has black-box property (Prf-BB for short) then HMAC f is Prf-BB.  ...  The pseudo-random oracle property assumes that a hash function is built from a publicly available FIL random function f (compression function).  ... 
doi:10.1007/978-3-642-27901-0_14 fatcat:bm33gh45yvdxplplcrizlvjlgu

Recycling physical random numbers

Art B. Owen
2009 Electronic Journal of Statistics  
Physical random numbers are not as widely used in Monte Carlo integration as pseudo-random numbers are. They are inconvenient for many reasons.  ...  Because of the symmetry, a small number B of replicates can be used to get confidence intervals based on the central limit theorem.  ...  Indeed the simulations in Section 4 were done with pseudo-random numbers.  ... 
doi:10.1214/09-ejs541 fatcat:tmro3qhqpra7jbx533zluyjnra

Pseudo-Derandomizing Learning and Approximation

Igor Carboni Oliveira, Rahul Santhanam, Michael Wagner
2018 International Workshop on Approximation Algorithms for Combinatorial Optimization  
Our goal is to simulate known randomized algorithms in these settings by pseudo-deterministic algorithms in a generic fashion -a goal we succinctly term pseudo-derandomization. Learning.  ...  In the setting of learning with membership queries, we first show that randomized learning algorithms can be derandomized (resp. pseudo-derandomized) under the standard hardness assumption that E (resp  ...  These pseudo-derandomization results exploit specific properties of the known randomized algorithms for these problems.  ... 
doi:10.4230/lipics.approx-random.2018.55 dblp:conf/approx/OliveiraS18 fatcat:gjphuxvvubakxevkekyacqxryq

Reset Indifferentiability and Its Consequences [chapter]

Paul Baecher, Christina Brzuska, Arno Mittelbach
2013 Lecture Notes in Computer Science  
First, we show that any simulator satisfying the reset indifferentiability notion must be stateless and pseudo deterministic.  ...  The equivalence of the random-oracle model and the idealcipher model has been studied in a long series of results.  ...  via random oracles/ideal ciphers.  ... 
doi:10.1007/978-3-642-42033-7_9 fatcat:3w2fnx4rozh4lb44ic4ghgyqrq

Resource Tradeoffs and Derandomization [article]

Rahul Santhanam
2002 Electronic colloquium on computational complexity  
Finally, we give uniform assumptions under which there is a strict hierarchy for randomized polynomial time and randomized time can be simulated nontrivially by randomized space.  ...  We show similar tradeoffs between simulation of nondeterministic time by nondeterministic space and simulation of randomized algorithms by nondeterministic time.  ...  One approach to this problem is via the notion of pseudo-random generators, which are efficient deterministic procedures expanding short random seeds to strings that "look" random to algorithms from a  ... 
dblp:journals/eccc/ECCC-TR02-038 fatcat:h42lgx67lne5vbybtimpxwhxrq

Bayesian pseudo-empirical-likelihood intervals for complex surveys

J. N. K. Rao, Changbao Wu
2010 Journal of The Royal Statistical Society Series B-statistical Methodology  
The approach proposed compares favourably with a full Bayesian analysis under simple random sampling without replacement.  ...  For complex survey data, we show that a pseudo-empirical-likelihood approach can be used to construct Bayesian pseudo-empirical-likelihood intervals that are asymptotically valid under the design-based  ...  The Polya posterior is a flexible tool with reasonable design-based frequentist properties under simple random sampling, and it permits Bayesian interval estimation through simulation of finite populations  ... 
doi:10.1111/j.1467-9868.2010.00747.x fatcat:dw7rvqxgvrgkxhz76k5vjpncmy

Pseudo-deterministic Streaming [article]

Shafi Goldwasser, Ofer Grossman, Sidhanth Mohanty, David P. Woodruff
2019 arXiv   pre-print
A pseudo-deterministic algorithm is a (randomized) algorithm which, when run multiple times on the same input, with high probability outputs the same result on all executions.  ...  For example, in the instance of finding a nonzero entry in a vector, for any known low-space algorithm A, there exists a stream x so that running A twice on x (using different randomness) would with high  ...  We formally define a pseudo-deterministic streaming algorithm and show a pseudo-deterministic lower bound for Find-Duplicate to contrast with the randomized algorithm from Theorem 3.1.  ... 
arXiv:1911.11368v1 fatcat:ogsz743pmzhx7bmrryvagxkddu

On the Security of RSA Encryption in TLS [chapter]

Jakob Jonsson, Burton S. Kaliski
2002 Lecture Notes in Computer Science  
The reduction takes place in a security model with reasonable assumptions on the underlying TLS pseudo-random function, thereby addressing concerns about its construction in terms of two hash functions  ...  The second TKEM we consider follows this design, and we model only one of the pseudo-random functions as a random oracle and assume no specific properties of the other.  ...  The first TKEM is based on a single pseudo-random function, which we model as a random oracle.  ... 
doi:10.1007/3-540-45708-9_9 fatcat:grtdwhjlprgplp4nkaax355hgu

Random Number Generators: A Survival Guide for Large Scale Simulations [article]

Stephan Mertens
2009 arXiv   pre-print
In this lecture we will learn just enough of the theory of pseudo random number generation to make wise decisions on how to choose and how to use random number generators when it comes to large scale,  ...  parallel simulations.  ...  The quality issue arises because simulations only approximate randomness by generating a stream of deterministic numbers, named pseudo-random numbers, with successive calls to a subroutine called pseudo-random  ... 
arXiv:0905.4238v2 fatcat:mnb3l45zera2dgv72vwuosfeem

Verifiable Random Functions: Relations to Identity-Based Key Encapsulation and New Constructions

Michel Abdalla, Dario Catalano, Dario Fiore
2013 Journal of Cryptology  
that we call pseudo-random decapsulation.  ...  In a nutshell, pseudo-random decapsulation means that if one decapsulates a ciphertext C, produced with respect to an identity ID, using the decryption key corresponding to any other identity ID , the  ...  So, we are left with proving pseudo-random decapsulation in the following theorem. Theorem 5.  ... 
doi:10.1007/s00145-013-9153-x fatcat:bcexjhyymbfgvjp5q7efiwh7xi

Characterization Theorems for Pseudo-Variograms [article]

Christopher Dörr, Martin Schlather
2021 arXiv   pre-print
Pseudo-variograms appear naturally in the context of multivariate Brown-Resnick processes, and are a useful tool for analysis and prediction of multivariate random fields.  ...  We give a necessary and sufficient criterion for a matrix-valued function to be a pseudo-variogram, and further provide a Schoenberg-type result connecting pseudo-variograms and multivariate correlation  ...  Define an m-variate random field Z̃ via Z̃i (x) = Zi (x) − Z1 (0), x ∈ Rd , i = 1, . . . , m.  ... 
arXiv:2112.02595v1 fatcat:px7tttwdtrgj5cdylavsl7foum

On Sequence Lengths of Some Special External Exclusive OR Type LFSR Structures – Study and Analysis

A Ahmad, A Al Maashri
2014 The Journal of Engineering Research  
The outcomes of this paper are presented in the form of theorems, simulations, and analyses.  ...  Given that determining the length of generated pseudo-random binary sequence is a complex task, therefore, before using an LFSR structure, it is essential to investigate the length and the properties of  ...  In addition, Table 7 demonstrates the balance properties of the LFSR structures defined via Theorems 4 and 5.  ... 
doi:10.24200/tjer.vol11iss2pp1-14 fatcat:z2j7rz3x7rhajgkvne3myxm2yq

Matrix completion based MIMO radars with clutter and interference mitigation via transmit precoding

Bo Li, Athina P. Petropulu
2017 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
The derived performance guarantees hold for any random unitary waveforms and radar precoder.  ...  We show that the corresponding data matrix has a good incoherent property, which guarantees accurate reconstruction of the data matrix from partial entries.  ...  Based on Theorem 3, the radar precoder P can be designed without affecting the incoherence property of M.  ... 
doi:10.1109/icassp.2017.7952750 dblp:conf/icassp/LiP17a fatcat:lvs4gxymo5e7zozevz6kagqlwu
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