Andrea Gadotti Imperial College London University of Oxford
Luc Rocher Imperial College London University of Oxford
Florimond Houssiau Imperial College London
Alan Turing Institute
Ana-Maria Creţu Imperial College London
Yves-Alexandre de Montjoye Imperial College London
Source
Science Advances
Vol 10, Issue 29 17 June 2024
DOI: 10.1126/sciadv.adn7053
Abstract
Information about us, our actions, and our preferences is created at scale through surveys or scientific studies or as a result of our interaction with digital devices such as smartphones and fitness trackers. The ability to safely share and analyze such data is key for scientific and societal progress. Anonymization is considered by scientists and policy-makers as one of the main ways to share data while minimizing privacy risks. In this review, we offer a pragmatic perspective on the modern literature on privacy attacks and anonymization techniques. We discuss traditional de-identification techniques and their strong limitations in the age of big data. We then turn our attention to modern approaches to share anonymous aggregate data, such as data query systems, synthetic data, and differential privacy. We find that, although no perfect solution exists, applying modern techniques while auditing their guarantees against attacks is the best approach to safely use and share data today.
Table 2. Types of attacks on aggregate data Source: 10.1126/sciadv.adn7053
Gary Price (gprice@gmail.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area.
He earned his MLIS degree from Wayne State University in Detroit.
Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com.
