Big Data
As you may already know, IRI DarkShield produces search annotations and masking results with every operation. These log files can contain a large volume of data, including:
metadata about the file/database source(s) what data was found as a match which matcher matched the data how the data was masked (if it was) where matches occurred within each file or database. Read More
Data Masking/Protection
Abstract: HIPAA, GDPR, FERPA, and other data privacy laws require that personally identifiable information (PII) and related data considered sensitive be protected from disclosure or discovery. Read More
Data Masking/Protection
Article 17 of the General Data Protection Regulation (GDPR) stipulates the need to minimize aging data through deletion, as well as the ad hoc Right to Erasure, often referred to as the Right to be Forgotten. 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
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
Enterprise data continues to change rapidly in form, size, use, and residence. Rarely does it remain in siloed constructs anymore, limited to certain business units or untouched by the outside world. Read More