Privacy-Preserving Data Analysis on Graphs and Social Networks

While literature within the field of privacy-preserving data mining (PPDM) has been around for many years, attention has mostly been given to the perturbation and anonymization of tabular data; understanding the role of privacy over graphs and networks is still very much in its infancy. In this chapter, we survey a very recent body of research on privacy-preserving data analysis over graphs and networks in an effort to allow the reader to observe common themes and future directions.

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