Pseudonymisation Techniques
- Justus Ortlepp (Unlicensed)
- Laurence Reeve
| ATTENTION: This page has been migrated to the Tazama GitHub repository and is now located at: This page will no longer be maintained in Confluence. |
|---|
Whichever technique is employed, pseudonymisation must be unambiguously reversible.
Single-identifier Pseudonymisation
Counter
An identifier (the data that identifies a data subject) is substituted by a unique number chosen by a monotonic counter. First, an inception seed 𝑠 is set to an arbitrary value, such as 0, and then it is incremented before being assigned to represent an identifier.
Random Number Generator
This approach is similar to the counter with the difference that a random number is assigned to the identifier. Two options are available to create this mapping: a true random number generator or a cryptographic pseudo-random generator. Collisions must be resolved to ensure unambiguous reversal.
Cryptographic Hash Function
A cryptographic hash function takes input strings of arbitrary length (i.e. identifiers) and maps them to fixed
length outputs. A cryptographic hash function is directly applied to the identifier to obtain the corresponding pseudonym: 𝑃𝑠𝑒𝑢𝑑𝑜 = 𝐻(𝐼𝑑).
Message Authentication Code
This primitive can be seen as a keyed-hash function. It is very similar to the previous solution except that a secret key is introduced to generate the pseudonym. Without the knowledge of this key, it is not possible to map the identifiers and the pseudonyms.
Deterministic Encryption
Symmetric (deterministic) encryption and in particular block ciphers like the AES are used to encrypt an identifier using a secret key, which is both the pseudonymisation secret and the recovery secret.
Probabilistic Encryption
Probabilistic encryption is the use of randomness in an encryption algorithm so that when encrypting the same identifier several times it will, in general, yield different pseudonyms.