Matrix Theoretic Questions in Data Privacy

Add to your list(s) Download to your calendar using vCal

• Oliver Mason (Maynooth University, Ireland)
• Thursday 18 January 2018, 12:00-13:00
• Lecture Theatre 2, Strathcona Building.

If you have a question about this talk, please contact Sergey Sergeev.

Recent developments in areas such as Big Data, Smart Cities and the Internet of Things have led to the generation and processing of vast quantities of data: much of which contains personal information on users of these systems. As public awareness of the privacy implications of these technologies increases, there is a recognised need to develop formal mechanisms to protect the privacy of individual users. In recent years, several such formalisms have been proposed, including: k-anonymity; l-diversity; t-closeness; opacity; and differential privacy. In this talk, I will discuss a number of matrix theoretic questions that naturally arise in connection with several of these privacy paradigms. In particular, I will describe recent results on a matrix polytope associated with differential privacy for discrete databases, as well as problems and results related to the design of privacy preserving positive observers for positive linear systems.

This talk is part of the Optimisation and Numerical Analysis Seminars series.

This talk is included in these lists:

• Lecture Theatre 2, Strathcona Building
• Optimisation and Numerical Analysis Seminars
• School of Mathematics events

Note that ex-directory lists are not shown.