Standard

Combining PBFT and Raft for Scalable and Fault-tolerant Distributed Consensus. / Дик, Александр Геннадьевич; Богданов, Александр Владимирович; Щеголева, Надежда Львовна; Киямов, Жасур Уткирович; Хватов, Валерий.

в: Physics of Particles and Nuclei, Том 55, № 3, 2024, стр. 418–420.

Результаты исследований: Научные публикации в периодических изданиях › статья в журнале по материалам конференции › Рецензирование

Harvard

Дик, АГ, Богданов, АВ, Щеголева, НЛ, Киямов, ЖУ & Хватов, В 2024, 'Combining PBFT and Raft for Scalable and Fault-tolerant Distributed Consensus', Physics of Particles and Nuclei, Том. 55, № 3, стр. 418–420. https://doi.org/10.1134/S1063779624030225

APA

Дик, А. Г., Богданов, А. В., Щеголева, Н. Л., Киямов, Ж. У., & Хватов, В. (2024). Combining PBFT and Raft for Scalable and Fault-tolerant Distributed Consensus. Physics of Particles and Nuclei, 55(3), 418–420. https://doi.org/10.1134/S1063779624030225

Vancouver

Дик АГ, Богданов АВ, Щеголева НЛ, Киямов ЖУ, Хватов В. Combining PBFT and Raft for Scalable and Fault-tolerant Distributed Consensus. Physics of Particles and Nuclei. 2024;55(3):418–420. https://doi.org/10.1134/S1063779624030225

Author

Дик, Александр Геннадьевич ; Богданов, Александр Владимирович ; Щеголева, Надежда Львовна ; Киямов, Жасур Уткирович ; Хватов, Валерий. / Combining PBFT and Raft for Scalable and Fault-tolerant Distributed Consensus. в: Physics of Particles and Nuclei. 2024 ; Том 55, № 3. стр. 418–420.

BibTeX

@article{00274bcfc13247c6a4d290739fdb51e0,
title = "Combining PBFT and Raft for Scalable and Fault-tolerant Distributed Consensus",
abstract = "Ensuring the confidentiality and protection of personal information in big data is an important aspect in data processing. One of the effective methods to achieve a high level of protection is depersonalization of data. The article presents an overview of modern methods of preserving personal data when conducting various kinds of research, in business analytics, etc.. To reduce the probability of data de-identification, a hashing method based on the use of the Kessak-256 hash function and the addition of a dynamic random string for each dataset element is proposed. This method allows you to significantly increase the time of hacking and the amount of resources required by the attacker. This approach can be used for secure data transmission, exchange and storage",
author = "Дик, {Александр Геннадьевич} and Богданов, {Александр Владимирович} and Щеголева, {Надежда Львовна} and Киямов, {Жасур Уткирович} and Валерий Хватов",
year = "2024",
doi = "10.1134/S1063779624030225",
language = "English",
volume = "55",
pages = "418–420",
journal = "Physics of Particles and Nuclei",
issn = "1063-7796",
publisher = "МАИК {"}Наука/Интерпериодика{"}",
number = "3",
note = "null ; Conference date: 03-07-2023 Through 07-07-2023",
url = "https://indico.jinr.ru/event/3505/",

}

RIS

TY - JOUR

T1 - Combining PBFT and Raft for Scalable and Fault-tolerant Distributed Consensus

AU - Дик, Александр Геннадьевич

AU - Богданов, Александр Владимирович

AU - Щеголева, Надежда Львовна

AU - Киямов, Жасур Уткирович

AU - Хватов, Валерий

N1 - Conference code: 10

PY - 2024

Y1 - 2024

N2 - Ensuring the confidentiality and protection of personal information in big data is an important aspect in data processing. One of the effective methods to achieve a high level of protection is depersonalization of data. The article presents an overview of modern methods of preserving personal data when conducting various kinds of research, in business analytics, etc.. To reduce the probability of data de-identification, a hashing method based on the use of the Kessak-256 hash function and the addition of a dynamic random string for each dataset element is proposed. This method allows you to significantly increase the time of hacking and the amount of resources required by the attacker. This approach can be used for secure data transmission, exchange and storage

AB - Ensuring the confidentiality and protection of personal information in big data is an important aspect in data processing. One of the effective methods to achieve a high level of protection is depersonalization of data. The article presents an overview of modern methods of preserving personal data when conducting various kinds of research, in business analytics, etc.. To reduce the probability of data de-identification, a hashing method based on the use of the Kessak-256 hash function and the addition of a dynamic random string for each dataset element is proposed. This method allows you to significantly increase the time of hacking and the amount of resources required by the attacker. This approach can be used for secure data transmission, exchange and storage

UR - https://indico.jinr.ru/event/3505/contributions/21826/

U2 - 10.1134/S1063779624030225

DO - 10.1134/S1063779624030225

M3 - Conference article

VL - 55

SP - 418

EP - 420

JO - Physics of Particles and Nuclei

JF - Physics of Particles and Nuclei

SN - 1063-7796

IS - 3

Y2 - 3 July 2023 through 7 July 2023

ER -

ID: 113495249