Description: Scrambling is a method of altering data to prevent unauthorized access to sensitive information while preserving its utility for analysis and processing. This approach is based on modifying the original data in such a way that it becomes difficult to identify or associate with specific individuals, but without compromising its informational value. Through techniques such as substitution, masking, or perturbation, scrambling allows data to be used in environments where privacy is crucial, such as in research, market analysis, or artificial intelligence development. This process is fundamental in the context of data protection, as it helps comply with regulations like GDPR in Europe, which requires that adequate measures be implemented to safeguard personal information. In summary, scrambling not only protects individuals’ privacy but also facilitates the responsible use of data in various applications, ensuring that information can be analyzed without risking the confidentiality of the original data.
