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Comparative Analysis of Efficiency of Fibonacci Random Number Generator Algorithm and Gaussian Random Number Generator Algorithm in a Cryptographic System.

Ing. Edward Opoku-Mensah, Abilimi A. Christopher, Francis Ohene Boateng

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Abstract

Random Numbers determine the security level of Cryptographic Applications as they are used to generate padding schemes in the encryption and decryption process as well as used to generate cryptographic keys.The more randomness in the numbers a generator generates the more effective the cryptographic algorithm, and the more secured it is to be used for protecting confidential data.Sometimes developers find it difficult to determine which Random Number Generators (RNGs) can provide a much secured Cryptographic System for secured enterprise application implementations.Two of such random number generators include the Fibonacci Random Number Generator and the Gaussian Random Generator.The researchers sought to determine, between these two, the better to be used for improving data security in cryptographic software systems.The researchers employed statistical tests like Frequency test, Chi-Square test, Kolmogorov-Smirnov test on the first 100 random numbers between 0 and 1000 generated using the above generators.The research concluded that Fibonacci Random Number Generator is more efficient than the Gaussian Random Number Generator and therefore recommended the choice of Fibonacci Random Number Generator when choosing between the two for use in a cryptographic system for better data security.

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Random Numbers determine the security level of Cryptographic Applications as they are used to generate padding schemes in the encryption and decryption process as well as used to generate cryptographic keys.The more randomness in the numbers a generator generates the more effective the cryptographic algorithm, and the more secured it is to be used for protecting confidential data.Sometimes developers find it difficult to determine which Random Number Generators (RNGs) can provide a much secured Cryptographic System for secured enterprise application implementations.Two of such random number generators include the Fibonacci Random Number Generator and the Gaussian Random Generator.The researchers sought to determine, between these two, the better to be used for improving data security in cryptographic software systems.The researchers employed statistical tests like Frequency test, Chi-Square test, Kolmogorov-Smirnov test on the first 100 random numbers between 0 and 1000 generated using the above generators.The research concluded that Fibonacci Random Number Generator is more efficient than the Gaussian Random Number Generator and therefore recommended the choice of Fibonacci Random Number Generator when choosing between the two for use in a cryptographic system for better data security.

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Available abstract

Random Numbers determine the security level of Cryptographic Applications as they are used to generate padding schemes in the encryption and decryption process as well as used to generate cryptographic keys.The more randomness in the numbers a generator generates the more effective the cryptographic algorithm, and the more secured it is to be used for protecting confidential data.Sometimes developers find it difficult to determine which Random Number Generators (RNGs) can provide a much secured Cryptographic System for secured enterprise application implementations.Two of such random number generators include the Fibonacci Random Number Generator and the Gaussian Random Generator.The researchers sought to determine, between these two, the better to be used for improving data security in cryptographic software systems.The researchers employed statistical tests like Frequency test, Chi-Square test, Kolmogorov-Smirnov test on the first 100 random numbers between 0 and 1000 generated using the above generators.The research concluded that Fibonacci Random Number Generator is more efficient than the Gaussian Random Number Generator and therefore recommended the choice of Fibonacci Random Number Generator when choosing between the two for use in a cryptographic system for better data security.

Key concepts: Random number generation, Computer science, Cryptography, Encryption, Algorithm, Fibonacci number, Random seed, Randomness tests

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Comparative Analysis of Efficiency of Fibonacci Random Number Generator Algorithm and Gaussian Random Number Generator Algorithm in a Cryptographic System. — Research Paper | ScholarLens