Excellent example of failed "anonymisation" of a dataset
january 2015 by jm
Fred Logue notes how this failed Mayo TD Michelle Mulherin:data anonymisation fred-logue ireland michelle-mulherin tds kenya data-protection privacy
From recent reports it mow appears that the Department of Education is discussing anonymisation of the Primary Online Database with the Data Protection Commissioner. Well someone should ask Mayo TD Michelle Mulherin how anonymisation is working for her.
The Sunday Times reports that Ms Mulherin was the only TD in the Irish parliament on the dates when expensive phone calls were made to a mobile number in Kenya. The details of the calls were released under the Freedom of Information Act in an “anonymised” database. While it must be said the fact that Ms Mulherin was the only TD present on those occasions does not prove she made the calls – the reporting in the press is now raising the possibility that it was her.
From a data protection point of view this is a perfect example of the difficulty with anonymisation. Data protection rules apply to personal data which is defined as data relating to a living individual who is or can be identified from the data or from the data in conjunction with other information. Anonymisation is often cited as a means for processing data outside the scope of data protection law but as Ms Mulherin has discovered individuals can be identified using supposedly anonymised data when analysed in conjunction with other data.
In the case of the mysterious calls to Kenya even though the released information was “anonymised” to protect the privacy of public representatives, the phone log used in combination with the attendance record of public representatives and information on social media was sufficient to identify individuals and at least raise evidence of association between individuals and certain phone calls. While this may be well and good in terms of accounting for abuses of the phone service it also has worrying implications for the ability of public representatives to conduct their business in private.
The bottom line is that anonymisation is very difficult if not impossible as Ms Mulherin has learned to her cost. It certainly is a lot more complex than simply removing names and other identifying features from a single dataset. The more data that there is and the more diverse the sources the greater the risk that individuals can be identified from supposedly anonymised datasets.
january 2015 by jm
Copy this bookmark: