Data Anonymization Defined
Data anonymization is the process of protecting private or sensitive information. It is done through the process of either encrypting or removing personally identifiable information from a database.
- Encrypting – using technology to render sensitive information as unreadable or unintelligible and can only be read after application of a decryption key, which must be kept separate from the encrypted files
- Removing – removing entire fields of data to reduce the risk of linking it to any source.
The purpose of data anonymization is to protect an individual or companies information or activity while ensuring and maintaining the integrity of the data gathered and shared.
To anonymize individual and company data, techniques include:
- Data Masking – hiding data with altered values
- Pseudonymization – data management and de-identification method that replaces private identifiers with fake identifiers or pseudonyms
- Generalization – deliberately removes some of the data to make it less identifiable
- Data Swapping – rearrange the dataset attribute values so they don’t correspond with the original records
- Data Perturbation – modifies the original dataset slightly by applying techniques that round numbers and add random noise
Software programs that are currently available to anonymize data include ARX, Anonymizer and Aircloak.
In Data Defined, we help make the complex world of data more accessible by explaining some of the most complex aspects of the field.
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