Data Masking in Practice

This article takes a strategic look at common data masking and anonymization techniques, and the challenges inherent in protecting certain types of sensitive and personal data, while ensuring that it still looks like the real data, and retains its referential integrity, and distribution characteristics. It also explains, briefly, with references, the tools that one can use to mask different types of data and how to provision development and test machines with these 'de-sensitized' databases, or alternatively to produce fake data that looks like the real thing, but in fact is generated randomly. Read more