De-Identification Requires a Platform Approach
The scope of data, users and purposes in your enterprise is vast. You need a data privacy platform that can meet the requirements for every context; a simple one size fits all using only data masking or data tokenization will fall flat.
That’s why the Privitar Data Privacy Platform™ enables you to select from the full range of de-identification techniques in any combination so you can tune the data resolution and re-identification risk according to each individual analysis, model or use.
Access Privitar’s Guide to Data De-Identification
The Privitar Data De-identification 101 series provides a ground-level introduction to the issues surrounding data de-identification, one of the fundamental components of data privacy.
Understand Data Context
A successful data privacy program takes full account of data context. Context includes:- Dataset required for each analysis/model
- Combinations of direct and quasi-identifiers
- Different access rights and privileges of the employees and third parties
- Data users’ access to other datasets that could be used in a linkage attack
- The questions asked and insights sought
De-Identification Techniques
Once you understand the data context, you are equipped to select and apply the right techniques from Privitar’s full roster in any combination to the direct and quasi-identifiers.- Data Tokenization
- Data Encryption
- Data Generalization
- Data Masking
- Perturbation
- Redaction
- Substitution
Advanced Capabilities
It’s not just about having the full set of deidentification techniques from which to choose for a given data context. Privitar also provides you the flexibility to decide when to preserve consistency, format and reversibility. For advanced data privacy programs, only the Privitar Data Privacy Platform layers on the capabilities of SecureLink™ and differential privacy – giving you the power to safely combine, share or release data.
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