I'm trying to understand the difference between masked and tokenized data in the context of natural language processing. Could someone explain the background and purpose of these two techniques?
6
answers
DavidJohnson
Sun Mar 23 2025
Data masking is a technique used to alter the values of data.
CryptoVanguard
Sun Mar 23 2025
The purpose of data masking is to conceal the original values of the data.
BenjaminMoore
Sun Mar 23 2025
Once data has been masked, it is not possible to reverse the process.
KatanaSharpness
Sat Mar 22 2025
This means that the actual values of the data cannot be retrieved.
SeoulSerenitySeeker
Sat Mar 22 2025
In contrast, tokenized data involves the use of a token vault.