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669
Saving Private Randomness in OneWay Functions and Pseudorandom Generators
, 2007
"... Can a oneway function f on n input bits be used with fewer than n bits while retaining comparable hardness of inversion? We show that the answer to this fundamental question is negative, if one is limited blackbox reductions. Instead, we ask whether one can save on secret random bits at the expens ..."
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Cited by 4 (0 self)
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pseudorandom generator based on any regular oneway function with output range of known size 2 k. The construction requires a seed of only 2n + O(k log k) bits (as opposed to O(n log n) in previous constructions); the savings come from the reusability of public randomness. The secret part of the seed
Design and Analysis of /dev/random, a Pseudorandom Number Generator
, 2005
"... The ability to produce random numbers is an important aspect of many cryptographic applications. This document examines a method of constructing an algorithm that behaves in a nondeterministic manner in order to produce unpredictable outputs. Specifically, this paper examines the design of the pseu ..."
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of the pseudo random number generator /dev/random. 1 PRNG’s and the importance of randomness In many cryptographic applications, security relies on random numbers. Designers have built systems assuming the availability of random looking numbers to use as nonces [2], session keys, and salts to name a few
강원대학교 A Segmented LeapAhead LFSR PseudoRandom Number Generator
"... A LFSR is commonly used for various stream cryptography applications to generate random numbers. A Leapahead LFSR was presented to generate a multibits random number per cycle. It only requires a single LFSR and it has an advantages in hardware complexity. However, it suffers from the significant ..."
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A LFSR is commonly used for various stream cryptography applications to generate random numbers. A Leapahead LFSR was presented to generate a multibits random number per cycle. It only requires a single LFSR and it has an advantages in hardware complexity. However, it suffers from the significant
ELECTRONICS ELEKTRONIKA Unpredictable Cryptographic PseudoRandom Number Generator based on Nonlinear Dynamic Chaotic System
"... Hardware noise generators, for example [1,2], are very useful and perspective for the cryptographic applications. But nevertheless the application of hardware noise generators has a very high implementation cost. ..."
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Hardware noise generators, for example [1,2], are very useful and perspective for the cryptographic applications. But nevertheless the application of hardware noise generators has a very high implementation cost.
Using objectoriented typing to support architectural design in the C2 style
 In Proceedings of ACM SIGSOFT’96: Fourth Symposium on the Foundations of Software Engineering (FSE4
, 1996
"... Abstract Software architectures enable largescale software development. Component reuse and substitutability, two key aspects of largescale development, must be planned for during software design. Objectoriented (OO) type theory supports reuse by structuring intercomponent relationships and ve ..."
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Cited by 74 (18 self)
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and verifying those relationships through type checking in an architecture definition language (ADL). In this paper, we identify the issues and discuss the ramifications of applying OO type theory to the C2 architectural style. This work stems from a series of experiments that were conducted to investigate
Proceedings of the 2 nd International Cyber Resilience Conference Abstract NOVEL PSEUDORANDOM NUMBER GENERATION USING VARIANT LOGIC FRAMEWORK
"... Cyber Security requires cryptology for the basic protection. Among different ECRYPT technologies, stream cipher plays a central role in advanced network security applications; in addition, pseudorandom number generators are placed in the core position of the mechanism. In this paper, a novel method ..."
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Cyber Security requires cryptology for the basic protection. Among different ECRYPT technologies, stream cipher plays a central role in advanced network security applications; in addition, pseudorandom number generators are placed in the core position of the mechanism. In this paper, a novel
APPLICATIONS ON
"... MonteCarlo simulations are common and inherently well suited to parallel processing, thus requiring random numbers that are also generated in parallel. We describe here a splitting approach for parallel random number generation. Various definitions of the MonteCarlo method have been given. As one ..."
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pseudorandom number generator. The basic computation typically involves a significant amount of calculation, so that the pseudorandom number generation itself represents a small fraction of the total computational effort. In theory, the accuracy of the method improves with the number of trials
The Impact of Pseudorandom Number Quality on PRnaPredict, a Parallel Genetic Algorithm for RNA Secondary Structure Prediction Track: Biological Applications
"... This paper presents a parallel version of RnaPredict, a genetic algorithm (GA) for RNA secondary structure prediction. The research presented here builds on previous work and examines the impact of three different pseudorandom number generators (PRNGs) on the GA’s performance. The three generators t ..."
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This paper presents a parallel version of RnaPredict, a genetic algorithm (GA) for RNA secondary structure prediction. The research presented here builds on previous work and examines the impact of three different pseudorandom number generators (PRNGs) on the GA’s performance. The three generators
A Survey and Empirical Comparison of Modern PseudoRandom Number Generators for Distributed Stochastic Simulations
"... Distributed stochastic simulations has become a popular tool for evaluating and testing complex stochastic dynamic systems. However there is some concern about the credibility of the final results of such simulation studies [11]. One of the important issues which need to be properly addressed for en ..."
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Cited by 1 (0 self)
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for ensuring validity of the final results from any simulation study is application of an appropriate source of randomness. In the case of distributed stochastic simulation, the quality of the final results is highly dependent on the underlying parallel PseudoRandom Number Generator (PRNG). Parallel PRNGs
POLYNOMIAL VERSUS MATRIX METHODS FOR LEAPAHEAD IN SHIFTREGISTER TYPE PSEUDORANDOM NUMBER GENERATORS
"... Abstract. We compare the cost of polynomial and matrix methods for leaping ahead an arbitrary amount in the period of shiftregister based pseudorandom number generators. It is well known that both methods are applicable in the binary shiftregister case. However, for modular shiftregisters with mod ..."
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Abstract. We compare the cost of polynomial and matrix methods for leaping ahead an arbitrary amount in the period of shiftregister based pseudorandom number generators. It is well known that both methods are applicable in the binary shiftregister case. However, for modular shift
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