Pseudo Random Number Generation: a Reinforcement Learning approach

Volume: 170, Pages: 1122 - 1127
Published: Jan 1, 2020
Abstract
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 software applications. Test suites are used to evaluate PRNGs quality by checking statistical properties of the generated sequences. Machine learning techniques are often used to break these generators, i.e....
Paper Details
Title
Pseudo Random Number Generation: a Reinforcement Learning approach
Published Date
Jan 1, 2020
Volume
170
Pages
1122 - 1127
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