Data Masking

Privitar data masking extends beyond pseudonymization and tokenization

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Data Masking ≄ Pseudonymization and Tokenization

Although often used interchangeably; data masking, pseudonymization and tokenization are different de-identification techniques. Although pseudonymization removes direct identifiers, it leaves indirect identifiers untouched, potentially including quasi-identifiers, and therefore is insufficient to de-identify data. Privitar’s masking capabilities extend beyond pseudonymization and tokenization.

Privitar’s Data Masking Capabilities Include

Data Tokenization

Usually used for personally identifiable information, random tokens can be substituted for sensitive data. Privitar data masking supports rich data tokenization capabilities allowing you to take control of linkability, format preservation and reversibility.

Data Generalization

Often used with data tokenization, generalization blurs quasi-identifiers replacing sensitive data with less precise values via binning, reformatting, rounding or truncating. Privitar data masking supports both manual and automatic data generalization.

Data Encryption

Privitar supports 256-bit encryption. You own the keys; Privitar does not manage the keys. That way they are safe and secure using your standard systems and processes.

Data Generation

Privitar enables you to generate dates, numbers, text and even credit card numbers. Privitar allows you to define precise format, range and other rules.

Data Perturbation

Whether it’s currencies, dates or times, you define the amplitude of the noise for any field in a dataset. Privitar ensures the distribution across the range is uniform so that the original values cannot be determined.

Simple Text Techniques

Sometimes, you just want a simple, straightforward masking technique to make text safe. Privitar provides support for partially or fully redacting text, as well as substituting text with name-value pairs you define.

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