A new computer-controlled platform for ADC-based true random number generator and its applications

IF 1.2 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Turkish Journal of Electrical Engineering and Computer Sciences Pub Date : 2019-04-01 DOI:10.3906/ELK-1806-167
Selçuk Coskun, I. Pehlivan, Akif Akgül, Bi̇lal Gürevi̇n
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引用次数: 8

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.
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一种基于adc的真随机数发生器计算机控制平台及其应用
加密技术的基础是随机数生成器(rng)。随着技术的不断发展,密码学的应用领域越来越多,因此对rng的需求也在迅速增加。rng可以分为伪随机数生成器和真随机数生成器两类。trng是使用不可预测和不可控的熵源并生成随机数的系统。在trng的设计过程中,当将属于所用熵源的模拟信号转换为数字数据时,通常会使用比较器、触发器、施密特触发器和adc。在本研究中,设计并实现了一个计算机控制的新型灵活平台,用于在基于adc的TRNG设计中寻找最合适的系统参数。作为该平台的示例应用,设计了6个不同的trng,分别使用连续时间混沌系统“中堂”的3个不同输出作为熵源。6个设计的trng生成的随机数序列,经过国际最高标准NIST800-22测试,全部通过。在新设计的平台的帮助下,基于adc的高质量trng可以快速开发,而且不需要专业知识。在复杂的嵌入式TRNG设计之前,设计了一个平台,通过比较来确定哪个熵源和参数更好。此外,该平台可用于教育目的,以解释如何工作基于adc的TRNG。这就是为什么它也可以作为工程教育的实验设置。
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来源期刊
Turkish Journal of Electrical Engineering and Computer Sciences
Turkish Journal of Electrical Engineering and Computer Sciences COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
2.90
自引率
9.10%
发文量
95
审稿时长
6.9 months
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.
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