Privacy Enhancing Technologies

What is k-anonymity? k-Anonymity is a privacy enhancing technology (PET) that works by combining large sets of data with similar attributes. In doing so, direct or indirect identifiers about any individual contributing to that data set are obscured, often through generalization or suppression of attributes. k-Anonymization is often referred to as the power of “hiding in the crowd,” and is useful in protecting against re-identification.

The difference between data masking vs. hashing is that data masking involves removing or hiding sensitive data using a different value that is similar in structure to the original data, while hashing uses a formula to generate a string of characters that is fixed in length. Since hashes are concise and unique, they make large data sets easier to compare, yet make reversal significantly more difficult, if not impossible.

What is tokenized data? Tokenized data refers to a piece of non-sensitive data with no intrinsic value, known as a token, that stands in for another piece of sensitive information. The concept is akin to using poker chips to represent money. Tokens are stored within a database, so only those with access to the database are able to derive the original information from the tokenized data.

Obfuscation of personally identifiable information (PII) limits exposure of the sensitive data in ways that still allows portions of it to be useful. An example of PII obfuscation is nulling a bank account number for anyone except those with authorization to see the full number. This is particularly necessary in instances of fraud detection and analysis, because it allows those involved in fraud investigations to reference exact account numbers, but prevents people in other, unrelated departments from seeing customers’ full account numbers.