The goal of privacy metrics is to measure the degree of privacy enjoyed by users in a system
and the amount of protection offered by privacy-enhancing technologies. In this way, privacy …

The collection and analysis of data are continuously growing due to the pervasiveness of
computing devices. The analysis of such information is fostering businesses and …

The growing popularity and development of data mining technologies bring serious threat to
the security of individual,'s sensitive information. An emerging research topic in data mining …

Location information of workers are usually required for optimal task allocation in mobile
crowdsensing, which however raises severe concerns of location privacy leakage. Although …

One of the biggest concerns of big data is privacy. However, the study on big data privacy is
still at a very early stage. We believe the forthcoming solutions and theories of big data …

The k-anonymity privacy requirement for publishing microdata requires that each
equivalence class (ie, a set of records that are indistinguishable from each other with respect …

The collection of digital information by governments, corporations, and individuals has
created tremendous opportunities for knowledge-and information-based decision making …

In recent years, privacy-preserving data mining has been studied extensively, because of
the wide proliferation of sensitive information on the internet. A number of algorithmic …

In this paper, we propose the first formal privacy analysis of a data anonymization process
known as the synthetic data generation, a technique becoming popular in the statistics …

Recently, as more and more social network data has been published in one way or another,
preserving privacy in publishing social network data becomes an important concern. With …