2023Mehmet Akif Ersoy Üniversitesi Fen Bilimleri Enstitüsü DergisiOpen access

Can Tesla Sphere be used for Random Number Generation?

Oğuzhan ARSLAN, İsmail Kırbaş

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Abstract

The use of random numbers to represent uncertainty and unpredictability is essential in many industries. This is crucial in disciplines such as computer science, cryptography and statistics, where the use of randomness helps to guarantee the security and reliability of systems and procedures. In computer science, random number generation is used to generate passwords, keys and other security tokens, as well as to add randomness to algorithms and simulations. According to recent research, the hardware random number generators used in billions of IoT devices do not generate enough entropy. This paper describes how raw data collected by IoT system sensors can be used to generate random numbers for cryptography systems and also examines the consequences of these random numbers. Colour, light and camera are used as sensors. Monobit and poker test results are analysed to measure the quality of randomness. Sequences were obtained with the method that gave quality values as a result of the analysis and these sequences were entered into the NIST and FIPS 140-1 randomness test packages. When the results of these two tests were analysed, it was observed that the sequences passed all tests successfully.

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The use of random numbers to represent uncertainty and unpredictability is essential in many industries. This is crucial in disciplines such as computer science, cryptography and statistics, where the use of randomness helps to guarantee the security and reliability of systems and procedures. In computer science, random number generation is used to generate passwords, keys and other security tokens, as well as to add randomness to algorithms and simulations. According to recent research, the hardware random number generators used in billions of IoT devices do not generate enough entropy. This paper describes how raw data collected by IoT system sensors can be used to generate random numbers for cryptography systems and also examines the consequences of these random numbers. Colour, light and camera are used as sensors. Monobit and poker test results are analysed to measure the quality of randomness. Sequences were obtained with the method that gave quality values as a result of the analysis and these sequences were entered into the NIST and FIPS 140-1 randomness test packages. When the results of these two tests were analysed, it was observed that the sequences passed all tests successfully.

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Available abstract

The use of random numbers to represent uncertainty and unpredictability is essential in many industries. This is crucial in disciplines such as computer science, cryptography and statistics, where the use of randomness helps to guarantee the security and reliability of systems and procedures. In computer science, random number generation is used to generate passwords, keys and other security tokens, as well as to add randomness to algorithms and simulations. According to recent research, the hardware random number generators used in billions of IoT devices do not generate enough entropy. This paper describes how raw data collected by IoT system sensors can be used to generate random numbers for cryptography systems and also examines the consequences of these random numbers. Colour, light and camera are used as sensors. Monobit and poker test results are analysed to measure the quality of randomness. Sequences were obtained with the method that gave quality values as a result of the analysis and these sequences were entered into the NIST and FIPS 140-1 randomness test packages. When the results of these two tests were analysed, it was observed that the sequences passed all tests successfully.

Key concepts: Randomness, Random number generation, Randomness tests, NIST, Computer science, Cryptography, Entropy (arrow of time), Pseudorandom number generator

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Can Tesla Sphere be used for Random Number Generation? — Research Paper | ScholarLens