Importance of knowledge fundamentals
The purpose of this article is to provide an overview of the fundamental terms and techniques related to data protection. The following table presents key concepts that will help in understanding various approaches to safeguarding data against unauthorized access and preventing the identification of individuals. By familiarizing yourself with these concepts, you will be better equipped to navigate the complexities of data privacy and apply the appropriate techniques in your work.
Anonymization terms
| Term | Definition |
| Anonymization | Transforming personal data to prevent identification of individuals. |
| Pseudonymization | Replacing personal data with pseudonyms to hinder identification. |
| Data Aggregation | Combining data to avoid identifying individuals. |
| Data Truncation | Removing parts of data that may lead to identification. |
| Cryptography | Securing data through encryption. |
| Data Minimization Principle | A principle that involves collecting only the personal data necessary to achieve a specific purpose, to minimize the risk of identification. |
| Redaction | The process of removing or obscuring portions of data, text, or documents to protect sensitive or personal information from being disclosed. |
| Data Synthesis | The generation of artificial data based on patterns from real data, which retains the statistical properties of the original but does not relate to real individuals. |
| Identifiable Data | Data that can directly identify an individual. |
| Potentially Identifiable Data | Data that could lead to identification when combined with other information. |
| Data Deletion | Completely removing data so it cannot be recovered. |
| Quasi-Anonymization | Removing direct identifiers, but data can be reconstituted with additional information. |
| Data Quantization | Transforming data into categories to reduce precision and identification risk. |
