Publishing datasets is a common practice in empirical research. However, the risk of de-anonymization of individuals in these datasets is a significant concern, especially when the data is highly sensitive. This thesis aims to investigate the presence of privacy related vulnerabilities in a large collection of datasets. The thesis will focus on quantifying the extent of vulnerabilities and attempt to categorize them into distinct types.