Data privacy has become an important topic of research. Ubiquitous databases and the eclosion of web technology eases the access to information. This information can be related to individuals, and, thus, sensitive information about users can be easily accessed by interested parties. Data privacy focuses on tools and methods to protect the privacy of the respondents and data owners. In the last years, a large number of methods have been developed for data privacy. Some of them are based on fuzzy sets and systems. In this position paper we present a review of some of our results in this area. In particular, we focus on the use of fuzzy sets for data protection, for measuring information loss and for measuring disclosure risk. The techniques used in this field and reviewed in this paper range from fuzzy clustering to fuzzy integrals.
Links:
[1] http://www.iiia.csic.es/en/individual/vicenc-torra
[2] http://www.iiia.csic.es/en/individual/daniel-abril
[3] http://www.iiia.csic.es/en/individual/guillermo-navarro-arribas
[4] http://www.atlantis-press.com/php/paper-details.php?from=author index&id=2328&querystr=
[5] http://www.iiia.csic.es/en/publications/keyword/Data privacy
[6] http://www.iiia.csic.es/en/publications/keyword/fuzzy clustering
[7] http://www.iiia.csic.es/en/publications/keyword/fuzzy measures
[8] http://www.iiia.csic.es/en/publications/keyword/fuzzy integrals
[9] http://www.iiia.csic.es/en/publications/export/tagged/4441
[10] http://www.iiia.csic.es/en/publications/export/xml/4441
[11] http://www.iiia.csic.es/en/publications/export/bib/4441
[12] http://www.iiia.csic.es/en/project/ares