Although often used interchangeably; masking, pseudonymization and tokenization are different. 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.
Usually used for direct identifiers, random tokens can be substituted for identifying data. Privitar supports rich tokenization capabilities allowing you to take control of linkability, format preservation and reversibility.
Often used in conjunction with tokenization, generalization blurs quasi-identifiers replacing data with less precise values via binning, reformatting, rounding or truncating. Privitar’s support for manual and automatic generalization has enhanced functionality for k-anonymity.
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.
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.
When synthetic data is required, Privitar enables you to generate dates, numbers, text and even credit card numbers. Plus Privitar allows you to define precise format, range and other rules to ensure system compatibility.
Sometimes, you just want a simple, straightforward 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.