Data anonymization is the process of removing or altering any information that can be used to identify an individual from a data set. This technique provides the strongest assurance that data does not identify an individual, as it makes it impossible or extremely difficult to link the data back to the original source. Data anonymization can be achieved by various methods, such as generalization, suppression, perturbation, or pseudonymization12. Data anonymization is often used for privacy protection, compliance with data protection regulations, and data sharing purposes3. References:
1: Data Security: Definition, Importance, and Types | Fortinet
2: Data Security Best Practices: Top 10 Data Protection Methods - Ekran System
3: Data anonymization - Wikipedia
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