Selçuk Coskun, I. Pehlivan, Akif Akgül, Bi̇lal Gürevi̇n
{"title":"一种基于adc的真随机数发生器计算机控制平台及其应用","authors":"Selçuk Coskun, I. Pehlivan, Akif Akgül, Bi̇lal Gürevi̇n","doi":"10.3906/ELK-1806-167","DOIUrl":null,"url":null,"abstract":"The basis of encryption techniques is random number generators (RNGs). The application areas of cryptology are increasing in number due to continuously developing technology, so the need for RNGs is increasing rapidly, too. RNGs can be divided into two categories as pseudorandom number generator (PRNGs) and true random number generator (TRNGs). TRNGs are systems that use unpredictable and uncontrollable entropy sources and generate random numbers. During the design of TRNGs, while analog signals belonging to the used entropy sources are being converted to digital data, generally comparators, flip-flops, Schmitt triggers, and ADCs are used. In this study, a computer-controlled new and flexible platform to find the most appropriate system parameters in ADC-based TRNG designs is designed and realized. As a sample application with this new platform, six different TRNGs that use three different outputs of Zhongtang, which is a continuous time chaotic system, as an entropy source are designed. Random number series generated with the six designed TRNGs are put through the NIST800–22 test, which has the internationally highest standards, and they pass all tests. With the help of the new platform designed, ADC-based high-quality TRNGs can be developed fast and also without the need for expertise. The platform has been designed to decide which entropy source and parameter are better by comparing them before complex embedded TRNG designs. In addition, this platform can be used for educational purposes to explain how to work an ADC-based TRNG. That is why it can be utilized as an experiment set in engineering education, as well.","PeriodicalId":49410,"journal":{"name":"Turkish Journal of Electrical Engineering and Computer Sciences","volume":"39 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"A new computer-controlled platform for ADC-based true random number generator and its applications\",\"authors\":\"Selçuk Coskun, I. Pehlivan, Akif Akgül, Bi̇lal Gürevi̇n\",\"doi\":\"10.3906/ELK-1806-167\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The basis of encryption techniques is random number generators (RNGs). The application areas of cryptology are increasing in number due to continuously developing technology, so the need for RNGs is increasing rapidly, too. RNGs can be divided into two categories as pseudorandom number generator (PRNGs) and true random number generator (TRNGs). TRNGs are systems that use unpredictable and uncontrollable entropy sources and generate random numbers. During the design of TRNGs, while analog signals belonging to the used entropy sources are being converted to digital data, generally comparators, flip-flops, Schmitt triggers, and ADCs are used. In this study, a computer-controlled new and flexible platform to find the most appropriate system parameters in ADC-based TRNG designs is designed and realized. As a sample application with this new platform, six different TRNGs that use three different outputs of Zhongtang, which is a continuous time chaotic system, as an entropy source are designed. Random number series generated with the six designed TRNGs are put through the NIST800–22 test, which has the internationally highest standards, and they pass all tests. With the help of the new platform designed, ADC-based high-quality TRNGs can be developed fast and also without the need for expertise. The platform has been designed to decide which entropy source and parameter are better by comparing them before complex embedded TRNG designs. In addition, this platform can be used for educational purposes to explain how to work an ADC-based TRNG. 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A new computer-controlled platform for ADC-based true random number generator and its applications
The basis of encryption techniques is random number generators (RNGs). The application areas of cryptology are increasing in number due to continuously developing technology, so the need for RNGs is increasing rapidly, too. RNGs can be divided into two categories as pseudorandom number generator (PRNGs) and true random number generator (TRNGs). TRNGs are systems that use unpredictable and uncontrollable entropy sources and generate random numbers. During the design of TRNGs, while analog signals belonging to the used entropy sources are being converted to digital data, generally comparators, flip-flops, Schmitt triggers, and ADCs are used. In this study, a computer-controlled new and flexible platform to find the most appropriate system parameters in ADC-based TRNG designs is designed and realized. As a sample application with this new platform, six different TRNGs that use three different outputs of Zhongtang, which is a continuous time chaotic system, as an entropy source are designed. Random number series generated with the six designed TRNGs are put through the NIST800–22 test, which has the internationally highest standards, and they pass all tests. With the help of the new platform designed, ADC-based high-quality TRNGs can be developed fast and also without the need for expertise. The platform has been designed to decide which entropy source and parameter are better by comparing them before complex embedded TRNG designs. In addition, this platform can be used for educational purposes to explain how to work an ADC-based TRNG. That is why it can be utilized as an experiment set in engineering education, as well.
期刊介绍:
The Turkish Journal of Electrical Engineering & Computer Sciences is published electronically 6 times a year by the Scientific and Technological Research Council of Turkey (TÜBİTAK)
Accepts English-language manuscripts in the areas of power and energy, environmental sustainability and energy efficiency, electronics, industry applications, control systems, information and systems, applied electromagnetics, communications, signal and image processing, tomographic image reconstruction, face recognition, biometrics, speech processing, video processing and analysis, object recognition, classification, feature extraction, parallel and distributed computing, cognitive systems, interaction, robotics, digital libraries and content, personalized healthcare, ICT for mobility, sensors, and artificial intelligence.
Contribution is open to researchers of all nationalities.