Year: 2019
Type: preprint
Abstract: Over the recent years, the availability of datasets containing personal, but anonymized information has been continuously increasing. Extensive research has revealed that such datasets are vulnerable to privacy breaches: being able to reveal sensitive information about individuals through deanonymization methods. Here, we provide a taxonomy of the research in de-anonymization.
Source: arXiv (Cornell University)
Authors: Bampoulidis, Alexandros, Lupu, Mihai
Institution: Research Studios Austria
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2915614643