Title: Statistical Disclosure Control and Differential Privacy
Speaker: Natalie Shlomo, University of Manchester

Abstract: For decades, statistical agencies have been disseminating statistical data in the form of microdata from social surveys and tabular data from censuses, surveys and registers. The Statistical Disclosure Control (SDC) literature covers a wide range of topics, including
the types of disclosure risks and possible attack scenarios, how to protect statistical data and the quantification of disclosure risk and data utility. However, these traditional forms of statistical data and their confidentiality protection rely heavily on assumptions that may no
longer be relevant. In recent years, we have seen the digitalization of all aspects of our society leading to new and linked data sources offering unprecedented opportunities for research and evidence-based policies. These developments have put pressure on statistical
agencies to provide broader and more open access to their data. On the other hand, with detailed personal information easily accessible from the internet, traditional SDC methods may no longer be sufficient and this has led to the opposite effect of statistical agencies
restricting and licensing data. To meet the demands and challenges for disseminating more open and accessible data, statistical agencies have been investigating more rigorous data protection mechanisms with stricter privacy guarantees to incorporate into their SDC toolkit. 
One such mechanism is Differential Privacy, a mathematically principled method of measuring how secure a protection mechanism is with respect to personal data disclosures. We present some future dissemination strategies under consideration by statistical agencies
and the potential for Differential Privacy to protect the confidentiality of data subjects with well-defined privacy guarantees.

Bio: Natalie Shlomo is Professor of Social Statistics at the University of Manchester. Her main areas of interest are in topics related to survey statistics and survey methodology. She has over 80 publications and refereed book chapters and a track record of generating external
funding for her research. She is an elected member of the International Statistical Institute (ISI), a fellow of the Royal Statistical Society, a fellow of the Academy of Social Sciences and President 2023-2025 of the International Association of Survey Statisticians.  She also
serves on national and international Methodology Advisory Committees and editorial boards.

Homepage:   https://www.research.manchester.ac.uk/portal/natalie.shlomo.html