论文信息 - Analysis of FIPS 140-2 Test and Chaos-Based Pseudorandom Number Generator

Analysis of FIPS 140-2 Test and Chaos-Based Pseudorandom Number Generator

Pseudo random numbers are used for various purposes. Pseudo random number generators (PRNGs) are useful tools to provide pseudo random numbers. The FIPS 140-2 test issued by the American National Institute of Standards and Technologyhas been widely used for the verications the statistical properties of the randomness of the pseudo random numbers generated by PRNGs. First this paper analyzes the FIPS 140-2 test. The results show that The required interval of the FIPS140-2 Monobit Test corresponds to the condent interval with signicant level

Lequan Min | Tianyu Chen | Hongyan Zang

[1] Elaine B. Barker,et al. A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications , 2000 .

[2] William M. Daley,et al. Security Requirements for Cryptographic Modules , 1999 .

[3] E. Lorenz. Deterministic nonperiodic flow , 1963 .

[4] Bruce Schneier,et al. Cryptography Engineering - Design Principles and Practical Applications , 2010 .

[5] Lequan Min,et al. Chaos criterion on some quadric polynomial maps and design for chaotic pseudorandom number generator , 2011, 2011 Seventh International Conference on Natural Computation.

[6] Gonzalo Álvarez,et al. Cryptanalysis of a chaotic block cipher with external key and its improved version , 2006, ArXiv.

[7] Stefan Wegenkittl,et al. Gambling tests for pseudorandom number generators , 2001 .

[8] Robert A. J. Matthews,et al. On the Derivation of a "Chaotic" Encryption Algorithm , 1989, Cryptologia.

[9] J. Sprott. Chaos and time-series analysis , 2001 .

[10] J. Yorke,et al. Period Three Implies Chaos , 1975 .

[11] L. Kocarev,et al. Chaos-based random number generators-part I: analysis [cryptography] , 2001 .

[12] Solomon W. Golomb,et al. Shift Register Sequences , 1981 .

[13] E. E. García-Guerrero,et al. Synchronization of Chua’s circuits with multi-scroll attractors: Application to communication , 2009 .

[14] Kurt Binder,et al. Monte Carlo Simulation in Statistical Physics , 1992, Graduate Texts in Physics.