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A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications

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TLDR
Some criteria for characterizing and selecting appropriate generators and some recommended statistical tests are provided, as a first step in determining whether or not a generator is suitable for a particular cryptographic application.
Abstract
: This paper discusses some aspects of selecting and testing random and pseudorandom number generators. The outputs of such generators may he used in many cryptographic applications, such as the generation of key material. Generators suitable for use in cryptographic applications may need to meet stronger requirements than for other applications. In particular, their outputs must he unpredictable in the absence of knowledge of the inputs. Some criteria for characterizing and selecting appropriate generators are discussed in this document. The subject of statistical testing and its relation to cryptanalysis is also discussed, and some recommended statistical tests are provided. These tests may he useful as a first step in determining whether or not a generator is suitable for a particular cryptographic application. The design and cryptanalysis of generators is outside the scope of this paper.

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Review: Digital image steganography: Survey and analysis of current methods

TL;DR: This paper provides a state-of-the-art review and analysis of the different existing methods of steganography along with some common standards and guidelines drawn from the literature and some recommendations and advocates for the object-oriented embedding mechanism.
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Random numbers certified by Bell's theorem.

TL;DR: It is shown that the non-local correlations of entangled quantum particles can be used to certify the presence of genuine randomness, and it is thereby possible to design a cryptographically secure random number generator that does not require any assumption about the internal working of the device.
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TestU01: A C library for empirical testing of random number generators

TL;DR: TestU01 as discussed by the authors is a software library implemented in the ANSI C language, and offering a collection of utilities for the empirical statistical testing of uniform random number generators (RNGs).
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Power-Up SRAM State as an Identifying Fingerprint and Source of True Random Numbers

TL;DR: It is demonstrated that a 512-byte SRAM fingerprint contains sufficient entropy to generate 128-bit true random numbers and that the generated numbers pass the NIST tests for runs, approximate entropy, and block frequency.
References
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Book

Handbook of Applied Cryptography

TL;DR: A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols.
Journal ArticleDOI

A universal statistical test for random bit generators

TL;DR: A new statistical test for random bit generators is presented which can detect any significant deviation of a device's output statistics from the statistics of a truly random bit source when the device can be modeled as an ergodic stationary source with finite memory but arbitrary (unknown) state transition probabilities.