University of Birmingham > Talks@bham > Optimisation and Numerical Analysis Seminars > Matrix Theoretic Questions in Data Privacy

Matrix Theoretic Questions in Data Privacy

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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.

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