Shuffling has been approved as a data de-identifcation technique by the EU Protection Board in Opinion on Anonymisation Techniques, 05/2014”. However, there has been very little discussion of appropriate use cases and risks. Talend, Informatica, Oracle and others support various forms of shuffling data and Fisher-Yates is a well-known algorithm.
Shuffling, similar to noise addition, may not provide full anonymisation by itself and usually is combined with other de-identification techniques.
Do examples of open public data exist where shuffling as been successfully used as a part of de-identification? Particular concerns with shuffling include which algorithm was used and how k-anonymization was applied to quasi-identifiers.