Statistics Seminar - Statistical Disclosure Control and Differential Privacy
| Dates: | 19 February 2025 |
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| Times: | 14:00 - 14:50 |
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| What is it: | Seminar |
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| Organiser: | Department of Mathematics |
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| Who is it for: | University staff, External researchers, Current University students |
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| Speaker: | Prof. Natalie Shlomo |
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Prof. 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 typology of disclosure risks and possible risk scenarios, the protection of 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.
Speaker
Prof. Natalie Shlomo
Organisation: Univ. of Manchester
Travel and Contact Information
Find event
Frank Adams 2
Alan Turing Building
Manchester
