Odds stacked against privacy, study shows
Bad news: you can easily be identified when giving anonymous personal data. Good news: it’s only 99.98% accurate.
Removing personal details from data to make it anonymous will not stop individuals being identified and compromising their privacy, a new study suggests.
Researchers from Imperial College London and the Catholic University of Louvain, Belgium, have shown that even so-called “anonymised” datasets – with names, addresses and other unique identifiers removed – can be traced back to individuals using statistical modelling.
The accuracy is unnerving: 99.98% of Americans could be re-identified in “anonymous” data that contained just 15 characteristics, including age, gender and marital status. The researchers say their findings, published in the journal Nature Communications, should be a wake-up call for policymakers on the need to tighten the rules for what constitutes truly anonymous data.
Anonymisation has been the main tool used by data collectors to address privacy concerns in the wake of scandals such as the sale of Facebook data to Cambridge Analytica.
But the new research shows how easily the data can be reverse engineered to re-identify individuals, using modelling based on statistical probability known as a generative copula-based method.
For example, a 61-year old man living in Chelsea, New York, would be correctly identified 81% of the time just from gender, birth date and postcode data. By adding just four more points of data (marital status, vehicle ownership, home ownership status and employment status) the likelihood of this person being correctly identified hits 100% as the combination of attributes becomes unique.
The more data points gathered, the easier it becomes to identify the individual behind the data – and some anonymous data sets contain as many as 248 data points.