PRNG Quality Assessment Methods Based on the Analysis of Generated Sequence Properties Using Visualisation

Autor:	Andrey V. Chirkin, Maxim M. Stepanov, Anton O. Prokofiev, Elizaveta M. Andronova, Kirill O. Simanovich
Rok vydání:	2021
Předmět:	Pseudorandom number generator Sequence Correctness Quality assessment Computer science media_common.quotation_subject computer.software_genre Mathematical proof Visualization Quality (business) Data mining computer media_common Visual methods
Zdroj:	2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus).
DOI:	10.1109/elconrus51938.2021.9396322
Popis:	The paper considers various methods for assessing the quality of pseudorandom number generators. We present visual methods for detecting anomalies, patterns, and deviations in pseudorandom sequences and define quality criteria for the presented methods. Also, we presented results of PRNG research by the proposed methods and proofs of the described methods correctness. Finally, we formulated recommendations to increase the effectiveness of the presented in research methods.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::041fe3fe0239be5c1d1e7704d5c55257 https://doi.org/10.1109/elconrus51938.2021.9396322 Zobrazit plný text záznamu