Protection of Personal Data Using Anonymization

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.