24,911 research outputs found
Yet Another Pseudorandom Number Generator
We propose a novel pseudorandom number generator based on R\"ossler attractor
and bent Boolean function. We estimated the output bits properties by number of
statistical tests. The results of the cryptanalysis show that the new
pseudorandom number generation scheme provides a high level of data security.Comment: 5 pages, 7 figures; to be published in International Journal of
Electronics and Telecommunications, vol.63, no.
Pseudorandom Generators for Low Sensitivity Functions
A Boolean function is said to have maximal sensitivity s if s is the largest number of Hamming neighbors of a point which differ from it in function value. We initiate the study of pseudorandom generators fooling low-sensitivity functions as an intermediate step towards settling the sensitivity conjecture. We construct a pseudorandom generator with seed-length 2^{O(s^{1/2})} log(n) that fools Boolean functions on n variables with maximal sensitivity at most s. Prior to our work, the (implicitly) best pseudorandom generators for this class of functions required seed-length 2^{O(s)} log(n)
Pseudorandomness via the discrete Fourier transform
We present a new approach to constructing unconditional pseudorandom
generators against classes of functions that involve computing a linear
function of the inputs. We give an explicit construction of a pseudorandom
generator that fools the discrete Fourier transforms of linear functions with
seed-length that is nearly logarithmic (up to polyloglog factors) in the input
size and the desired error parameter. Our result gives a single pseudorandom
generator that fools several important classes of tests computable in logspace
that have been considered in the literature, including halfspaces (over general
domains), modular tests and combinatorial shapes. For all these classes, our
generator is the first that achieves near logarithmic seed-length in both the
input length and the error parameter. Getting such a seed-length is a natural
challenge in its own right, which needs to be overcome in order to derandomize
RL - a central question in complexity theory.
Our construction combines ideas from a large body of prior work, ranging from
a classical construction of [NN93] to the recent gradually increasing
independence paradigm of [KMN11, CRSW13, GMRTV12], while also introducing some
novel analytic machinery which might find other applications
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An Evolutionary Approach to the Design of Controllable Cellular Automata Structure for Random Number Generation
Cellular Automata (CA) has been used in pseudorandom number generation over a decade. Recent studies show that two-dimensional (2-d) CA Pseudorandom Number Generators (PRNGs) may generate better random sequences than conventional one-dimensional (1-d) CA PRNGs, but they are more complex to implement in hardware than 1-d CA PRNGs. In this paper, we propose a new class of 1-d CA Controllable Cellular Automata (CCA) without much deviation from the structure simplicity of conventional 1-d CA. We give a general definition of CCA first and then introduce two types of CCA – CCA0 and CCA2. Our initial study on them shows that these two CCA PRNGs have better randomness quality than conventional 1-d CA PRNGs but their randomness is affected by their structures. To find good CCA0/CCA2 structures for pseudorandom number generation, we evolve them using the Evolutionary Multi-Objective Optimization (EMOO) techniques. Three different algorithms are presented in this paper. One makes use of an aggregation function; the other two are based on the Vector Evaluated Genetic Algorithm (VEGA). Evolution results show that these three algorithms all perform well. Applying a set of randomness tests on the evolved CCA PRNGs, we demonstrate that their randomness is better than that of 1-d CA PRNGs and can be comparable to that of two-dimensional CA PRNGs
Pseudorandom Strings from Pseudorandom Quantum States
A fundamental result in classical cryptography is that pseudorandom
generators are equivalent to one-way functions and in fact implied by nearly
every classical cryptographic primitive requiring computational assumptions. In
this work, we consider a variant of pseudorandom generators called quantum
pseudorandom generators (QPRGs), which are quantum algorithms that
(pseudo)deterministically map short random seeds to long pseudorandom strings.
We provide evidence that QPRGs can be as useful as PRGs by providing
cryptographic applications of QPRGs such as commitments and encryption schemes.
Our main result is showing that QPRGs can be constructed assuming the
existence of logarithmic-length quantum pseudorandom states. This raises the
possibility of basing QPRGs on assumptions weaker than one-way functions. We
also consider quantum pseudorandom functions (QPRFs) and show that QPRFs can be
based on the existence of logarithmic-length pseudorandom function-like states.
Our primary technical contribution is a method for pseudodeterministically
extracting uniformly random strings from Haar-random states.Comment: 45 pages, 1 figur
Security Analysis of DRBG Using HMAC in NIST SP 800-90
HMAC_DRBG is a deterministic random bit generator using
HMAC specified in NIST SP 800-90. The document claims that
HMAC_DRBG is a pseudorandom bit generator if HMAC is a pseudorandom
function. However, no proof is given in the document. This article
provides a security analysis of HMAC_DRBG and confirms the claim
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