Data Masking/Protection
The Data Class Database Masking Job wizard in IRI Workbench can be used with an IRI FieldShield or Voracity license to mask PII in multiple, disparate database sources that have been previously classified. Read More
Big Data
Finding and masking personally identifiable information (PII) in Snowflake® data warehouses works the same way in IRI FieldShield® or Voracity® installations as it does for other relational database sources. Read More
Data Masking/Protection
“Have you stopped speeding?” You could probably object to a leading question like this in court, but what happens when an important question with only a yes or no answer is solicited on a mandatory form, and the response becomes part of an actionable database record? Read More
Data Masking/Protection
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. Read More
Data Masking/Protection
Adding ‘random noise’ to data through blurring or perturbation is a data common anonymization requirement for researchers and marketers of protected health information (PHI) seeking to comply with the HIPAA Expert Determination Method security rule. Read More
Data Masking/Protection
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). Read More
Data Masking/Protection
This article demonstrates the manipulation of a CSV file using an IRI Workbench wizard. In fact, this example shows how PII can be masked from almost any IRI job wizard, though CSV file masking is most often performed from a single or multi-file IRI FieldShield job menu. Read More
Data Masking/Protection
One of the biggest concerns with releasing a dataset is the risk that a potential attacker can identify the owners of particular records. Even though masking or removing unique identifiers, like names and Social Security Numbers, can reduce that risk substantially, it may still not be enough. Read More
Data Masking/Protection
IRI has discussed startpoint security in further detail with the Outlook Series in a segment about data masking.
This article defines what we’d like to call “startpoint security” mostly by virtue of a comparison to endpoint security. Read More
Big 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. Read More