конфіденційність

The article analyzes and compares personal data anonymization methods using k-anonymity, ℓ- diversity, and t-closeness as examples. The aim of the research is to evaluate the effectiveness of these methods in ensuring data privacy and identifying their vulnerabilities to re-identification attacks. The study was performed using the ARX Anonymization Tool on a test dataset containing personal income information.

ctive methods to protect personal data in online texts. Existing anonymization methods often prove ineffective against complex LLM analysis algorithms, especially when processing sensitive information such as medical data. This research proposes an innovative approach to anonymization that combines k-anonymity and adversarial methods. Our approach aims to improve the efficiency and speed of anonymization while maintaining a high level of data protection.

The author substantiates the relevance of digital forensics in the context of digitalisation of modern society, notes the active use of digital technologies in solving various types of illegal activities in the field of computer information, and defines the concepts of “digital trace” and “digital forensics”.

The article is devoted to the analysis of principles of mediation as an alternative method to ensure human and citizen’s rights, enshrined in the Law of Ukraine “On mediation”, their relationships and interdependence. The research methodology includes a complex analysis and consolidation of the available scientific and theoretical materials, as well as shaping the corresponding conclusions. In the process of the research conducting, the authors used methods of scientific cognition: terminological, logical and semantic, functional, system and structural, logical and normative.