Anonymization
Anonymization
Anonymization (pronunciation: /ˌænəˌmaɪˈzeɪʃən/) is a process that removes personally identifiable information from data sets, so that the people whom the data describe remain anonymous.
Etymology
The term "anonymization" is derived from the Greek word "anōnumos" meaning "without a name" and the English suffix "-ization", indicating the action or process of making something.
Process
The process of anonymization involves either encrypting or removing personally identifiable information from data sets, so that the individuals whom the data describe cannot be identified. This is often done to protect individuals' privacy while still allowing data to be used for research and statistical purposes.
Methods
There are several methods of anonymization, including data masking, data swapping, noise addition, and pseudonymization. Each method has its own strengths and weaknesses, and the choice of method often depends on the specific requirements of the data set and the intended use of the anonymized data.
Related Terms
- Data Masking: A method of anonymization that involves replacing personally identifiable information in a data set with fictional, but realistic, information.
- Data Swapping: A method of anonymization that involves swapping values of attributes between records in a data set.
- Noise Addition: A method of anonymization that involves adding random noise to data in order to obscure the original data.
- Pseudonymization: A method of anonymization that involves replacing personally identifiable information in a data set with artificial identifiers or pseudonyms.
See Also
External links
- Medical encyclopedia article on Anonymization
- Wikipedia's article - Anonymization
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