Quasi-identifiers, or indirect identifiers, are personal attributes that are true about, but not necessarily unique, to an individual. Examples are one’s age or date of birth, race, salary, educational attainment, occupation, marital status and zip code.
Note: This article covers the third available IRI customer method for statically masking or encrypting PII in structured MongoDB collections through the IRI FieldShield product or IRI Voracity platform (both powered by IRI CoSort v10 and its support of the native MongoDB driver).
Editors Note, Q2’19: In addition to the method described below, there is now also available to IRI FieldShield (data masking product) or IRI Voracity (data management platform) users a Data Class Database Masking wizard, which can be used if you have pre-classified your data.
According to Simson L. Garfinkel at the NIST Information Access Division’s Information Technology Laboratory,
De-identification is not a single technique, but a collection of approaches, algorithms, and tools that can be applied to different kinds of data with differing levels of effectiveness.
Detecting additions and updates to database tables for data replication, ETL, PII masking, and other incremental data movement and manipulation activities can be automated in IRI Voracity workflows designed and run in IRI Workbench (WB).
The “New Multi Table Protection Job …” wizard in IRI Workbench described in this article is one of the ways that IRI FieldShield product (or IRI Voracity platform) users can automatically mask personally identifiable information (PII) in database columns that are part of a foreign key relationship, and thus preserve referential integrity between the tables.