The newly emerged machine learning (eg, deep learning) methods have become a strong
driving force to revolutionize a wide range of industries, such as smart healthcare, financial …

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 …

K-Anonymity has been proposed as a mechanism for protecting privacy in microdata
publishing, and numerous recoding" models" have been considered for achieving  …

A number of organizations publish microdata for purposes such as public health and
demographic research. Although attributes that clearly identify individuals, such as Name …

Continued advances in mobile networks and positioning technologies have created a strong
market push for location-based applications. Examples include location-aware emergency …

A reference to answer all your statistical confidentiality questions. This handbook provides
technical guidance on statistical disclosure control and on how to approach the problem of …

This paper presents a novel technique, anatomy, for publishing sensitive data. Anatomy
releases all the quasi-identifier and sensitive values directly in two separate tables …

Preserving individual privacy when publishing data is a problem that is receiving increasing
attention. According to the fc-anonymity principle, each release of data must be such that …

We study generalization for preserving privacy in publication of sensitive data. The existing
methods focus on a universal approach that exerts the same amount of preservation for all …