Common Anonymization Techniques and Their Limitations

Common anonymization techniques include data masking, pseudonymization, and aggregation. While each method offers a level of data protection, they also have limitations. For example, pseudonymization, which replaces identifiable information with artificial identifiers, can be reversed if additional information becomes available, leading to re-identification risks. Similarly, techniques like k-anonymity can compromise data utility, affecting the accuracy of analysis. Therefore, the effectiveness of these methods varies based on the context of their application and the evolving techniques in data re-identification.