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Project

Data Mining without Spilling the Beans: Preserving more than Privacy Alone

Researchers, governments, companies, and other organizations increasingly rely on data and data mining methods to generate new knowledge and insights. An important open question is how to ensure that this can be done effectively, while simultaneously safeguarding any sensitive information this data may contain.
The aim of this project is to study the preservation of sensitive information, generically speaking, during a data mining process. Initially the focus will lie on concepts and foundations. In a later stadium, the focus will shift to applications.

Date:1 Jan 2017 →  31 Dec 2020
Keywords:data protection, Data mining
Disciplines:Information systems, Distributed computing, Programming languages, Scientific computing, Applied mathematics in specific fields, Computer architecture and networks, Information sciences, Statistics and numerical methods, Visual computing, Other information and computing sciences, Theoretical computer science