Data quality and security issues are very closely related. To ensure a high level of reliability in distributed systems and resilience from external attacks, the process of consolidating distributed data is critical. For consolidated systems, the access process relies heavily on data preprocessing, which, in turn, allows them to be anonymized. The analysis of closely related processes of consolidation and anonymization allows us to offer a secure access platform for distributed data, which makes it possible to implement secure access systems that depend only on the type and format of the data. It turns out that in the program stack for working with data, optimization can be done only with the entire framework, but not with its components. In this paper we perform analysis of data security as a complex problem related to both data quality and system architectures used to protect personal data.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2021
Subtitle of host publication21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part VIII
EditorsOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Chiara Garau, Ivan Blečić, David Taniar, Bernady O. Apduhan, Ana Maria Rocha, Eufemia Tarantino, Carmelo Maria Torre
PublisherSpringer Nature
Pages447-459
Number of pages13
ISBN (Electronic)978-3-030-87010-2
ISBN (Print)978-3-030-87009-6
DOIs
StatePublished - 2021
Event21st International Conference on Computational Science and Its Applications, ICCSA 2021 - Virtual, Online, Italy
Duration: 13 Sep 202116 Sep 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12956 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Computational Science and Its Applications, ICCSA 2021
Abbreviated titleICCSA 2021
Country/TerritoryItaly
CityVirtual, Online
Period13/09/2116/09/21

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

    Research areas

  • Big Data, Data access, Data anonymization, Data consolidation, Data platforms

ID: 85454123