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Related papers: Guaranteeing the diversity of number generators

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This work shows that the cryptanalysis of the shrinking generator requires fewer intercepted bits than what indicated by the linear complexity. Indeed, whereas the linear complexity of shrunken sequences is between $A \cdot 2^(S-2)$ and $A…

Cryptography and Security · Computer Science 2010-05-04 Pino Caballero-Gil , Amparo Fúster-Sabater , M. Eugenia Pazo-Robles

Pseudo-Random Numbers Generators (PRNGs) are algorithms produced to generate long sequences of statistically uncorrelated numbers, i.e. Pseudo-Random Numbers (PRNs). These numbers are widely employed in mid-level cryptography and in…

Cryptography and Security · Computer Science 2019-12-30 Luca Pasqualini , Maurizio Parton

Many Random Number Generators (RNG) are available nowadays; they are divided in two categories, hardware RNG, that provide "true" random numbers, and algorithmic RNG, that generate pseudo random numbers (PRNG). Both types usually generate…

Information Theory · Computer Science 2018-09-28 Andrea C. G. Mennucci

The Diffie-Hellman key agreement protocol is based on taking large powers of a generator of a prime-order cyclic group. Some generators allow faster exponentiation. We show that to a large extent, using the fast generators is as secure as…

Cryptography and Security · Computer Science 2010-08-02 Boaz Tsaban

Pseudo-random number generators (PRNG) are a fundamental element of many security algorithms. We introduce a novel approach to their implementation, by proposing the use of generative adversarial networks (GAN) to train a neural network to…

Machine Learning · Computer Science 2018-10-02 Marcello De Bernardi , MHR Khouzani , Pasquale Malacaria

Quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of…

Quantum Physics · Physics 2016-08-29 Xiongfeng Ma , Xiao Yuan , Zhu Cao , Bing Qi , Zhen Zhang

Generating secure random numbers is vital to the security and privacy infrastructures we rely on today. Having a computer system generate a secure random number is not a trivial problem due to the deterministic nature of computer systems.…

Cryptography and Security · Computer Science 2018-04-10 JV Roig

This article investigates integer sequences that partition the sequence into blocks of various lengths - irregular arrays. The main result of the article is explicit formulas for numbering of irregular arrays. A generalization of Cantor…

Combinatorics · Mathematics 2023-10-31 Boris Putievskiy

We propose an automated verification technique for hypersafety properties, which express sets of valid interrelations between multiple finite runs of a program. The key observation is that constructing a proof for a small representative set…

Programming Languages · Computer Science 2019-05-23 Azadeh Farzan , Anthony Vandikas

Iterative numerical algorithms are typically equipped with a stopping criterion, where the iteration process is terminated when some error or misfit measure is deemed to be below a given tolerance. This is a useful setting for comparing…

Numerical Analysis · Computer Science 2014-12-04 Uri Ascher , Farbod Roosta-Khorasani

Diversity can significantly increase the resilience of systems, by reducing the prevalence of shared vulnerabilities and making vulnerabilities harder to exploit. Work on software diversity for security typically creates variants of a…

Cryptography and Security · Computer Science 2019-07-23 Scott D. Stoller , Yanhong A. Liu

Random number generators (RNG) are an important resource in many areas: cryptography (both quantum and classical), probabilistic computation (Monte Carlo methods), numerical simulations, industrial testing and labeling, hazard games,…

Quantum Physics · Physics 2015-05-27 Mario Stipcevic

Randomness is an invaluable resource in today's life with a broad use reaching from numerical simulations through randomized algorithms to cryptography. However, on the classical level no true randomness is available and even the use of…

Quantum Physics · Physics 2015-02-24 Mataj Pivoluska , Martin Plesch

The unpredictability of random numbers is fundamental to both digital security and applications that fairly distribute resources. However, existing random number generators have limitations-the generation processes cannot be fully traced,…

Quantum Random Number Generators provide true physical randomness based on quantum processes, essential for cryptographic and scientific applications. However, practical implementations face challenges in robustness and verifiability:…

Quantum Physics · Physics 2025-10-31 Rodrigo Piera , Gianluca De Santis , Agustin Sanchez , Yury Kurochkin , James A. Grieve

Ideal quantum random number generators (QRNGs) can produce algorithmically random and thus incomputable sequences, in contrast to pseudo-random number generators. However, the verification of the presence of algorithmic randomness and…

Quantum Physics · Physics 2021-01-06 John T. Kavulich , Brennan P. Van Deren , Maximilian Schlosshauer

We present a framework to understand GAN training as alternating density ratio estimation and approximate divergence minimization. This provides an interpretation for the mismatched GAN generator and discriminator objectives often used in…

Machine Learning · Computer Science 2016-12-09 Ben Poole , Alexander A. Alemi , Jascha Sohl-Dickstein , Anelia Angelova

Quantum random number generator harnesses the power of quantum mechanics to generate true random numbers, making it valuable for various scientific applications. However, real-world devices often suffer from imperfections that can undermine…

Quantum Physics · Physics 2023-12-07 Xing Lin , Rong Wang

We investigate the construction of weakly-secure index codes for a sender to send messages to multiple receivers with side information in the presence of an eavesdropper. We derive a sufficient and necessary condition for the existence of…

Information Theory · Computer Science 2016-11-17 Lawrence Ong , Badri N. Vellambi , Phee Lep Yeoh , Jörg Kliewer , Jinhong Yuan

A computer code can simulate a system's propagation of variation from random inputs to output measures of quality. Our aim here is to estimate a critical output tail probability or quantile without a large Monte Carlo experiment. Instead,…

Machine Learning · Statistics 2019-08-16 Hao Chen , William J. Welch