Healthcare is a rapidly evolving field. Such development creates opportunities to provide
better quality, evidence-based treatment, however, increasing privacy violations …

With the continuous increase in avenues of personal data generation, privacy protection has
become a hot research topic resulting in various proposed mechanisms to address this …

The application of machine learning techniques to large and distributed data archives might
result in the disclosure of sensitive information about the data subjects. Data often contain …

Since the emergence of coronavirus disease–2019 (COVID-19) outbreak, every country has
implemented digital solutions in the form of mobile applications, web-based frameworks …

K-anonymity is the most widely used approach to privacy preserving microdata which is
mainly based on generalization. Although generalization-based k-anonymity approaches …

Currently, a significant focus has been established on the privacy protection of multi-
dimensional data publishing in various application scenarios, such as scientific research …

Most data owners publish personal data for information consumers, which is used for hidden
knowledge discovery. But data publishing in its original form may be subjected to unwanted …

The rapid development of the mobile Internet coupled with the widespread use of intelligent
terminals have intensified the digitization of personal information and accelerated the …

In the modern era, data of diverse types (medical, financial, etc.) are outsourced from data
owner environments to the public domains for data mining and knowledge discovery …

In this paper, we propose and implement a novel anonymization model, called data-centric-
diversity, to effectively safeguard the privacy of individuals with considerably enhanced utility …