DOI: 10.57760/sciencedb.14757
title: DHVRF Algorithm Testing Dataset
title: DHVRF算法测试数据集

description: The DHVRF algorithm testing dataset is mainly used to test the characteristics of the DHVRF algorithm and its application in consensus mechanisms on different platforms. The DHVRF algorithm designed by the research team can support the operation of 5 types of consensus mechanisms on mainstream Intel and ARM platforms for high security level random number generation algorithms. To verify that the random numbers generated by the DHVRF method can be correctly validated. The project mainly deployed and tested the performance of DHVRF methods in general NIST software, including over 20 indicators such as frequency test, cumulative sum test, and run test. Collection plan: The folder name of the test dataset is "DHVRF algorithm test dataset/". The "DHVRF generated random number_2. txt" and "NIST software analysis result random number_2. txt" in this folder respectively refer to a verifiable random number generated by the DHVRF algorithm and the NIST software analysis result for that random number. In addition, the "DHVRF Algorithm" folder also includes a sub folder called "Analysis Results Summary of NIST Software", which records the analysis results of NIST software on an additional 50 random numbers ("Rxxx. txt"). Time and location: This dataset is test data collected by the research unit "Peking University" from 2021 to 2023. Equipment situation: Data collection is processed in the following environment: hardware environment: supports general computing platforms such as Intel and ARM; System environment: Windows 11 and Ubuntu 20.04. 
description: The DHVRF algorithm testing dataset is mainly used to test the characteristics of the DHVRF algorithm and its application in consensus mechanisms on different platforms. The DHVRF algorithm designed by the research team can support the operation of 5 types of consensus mechanisms on mainstream Intel and ARM platforms for high security level random number generation algorithms. To verify that the random numbers generated by the DHVRF method can be correctly validated. The project mainly deployed and tested the performance of DHVRF methods in general NIST software, including over 20 indicators such as frequency test, cumulative sum test, and run test. Collection plan: The folder name of the test dataset is "DHVRF algorithm test dataset/". The "DHVRF generated random number_2. txt" and "NIST software analysis result random number_2. txt" in this folder respectively refer to a verifiable random number generated by the DHVRF algorithm and the NIST software analysis result for that random number. In addition, the "DHVRF Algorithm" folder also includes a sub folder called "Analysis Results Summary of NIST Software", which records the analysis results of NIST software on an additional 50 random numbers ("Rxxx. txt"). Time and location: This dataset is test data collected by the research unit "Peking University" from 2021 to 2023. Equipment situation: Data collection is processed in the following environment: hardware environment: supports general computing platforms such as Intel and ARM; System environment: Windows 11 and Ubuntu 20.04.