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This paper discusses some aspects of selecting and testing random and pseudorandom number generators. The outputs of such generators may be 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 be 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 be useful as a first step in determining whether or not a generator is suitable for a particular cryptographic application. However, no set of statistical tests can absolutely certify a generator as appropriate for usage in a particular application, i.e., statistical testing cannot serve as a substitute for cryptanalysis. The design and cryptanalysis of generators is outside the scope of this paper.
Random number generators. --- Statistical hypothesis testing. --- Computer security. --- Data encryption (Computer science) --- Hypothesis test --- P-value --- Random number generator --- Statistical tests --- Hypothesis test --- P-value --- Random number generator --- Statistical tests
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longitudinal stability --- wave drag --- spectrum analysis --- water waves --- bending moments --- frames --- dynamic loads --- determination of stress --- tanker ships --- statistical tests --- longitudinal stability --- wave drag --- spectrum analysis --- water waves --- bending moments --- frames --- dynamic loads --- determination of stress --- tanker ships --- statistical tests
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This paper discusses some aspects of selecting and testing random and pseudorandom number generators. The outputs of such generators may be 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 be 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 be useful as a first step in determining whether or not a generator is suitable for a particular cryptographic application. However, no set of statistical tests can absolutely certify a generator as appropriate for usage in a particular application, i.e., statistical testing cannot serve as a substitute for cryptanalysis. The design and cryptanalysis of generators is outside the scope of this paper.
Random number generators. --- Statistical hypothesis testing. --- Computer security. --- Data encryption (Computer science) --- Hypothesis test --- P-value --- Random number generator --- Statistical tests
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681.3*G3 --- Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- 681.3*G3 Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- Statistique mathématique --- Mathematical statistics --- Mathematical models. --- Operating systems (Computers) --- Computer systems programs --- Covariance --- Diagrams --- Lattice design --- Least squares method --- Newton raphson method --- Probability distribution functions --- Random access computer storage --- Regression analysis --- Scaling --- Statistical tests --- Subroutine libraries --- Translator routines
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