The increasing volume of personal and sensitive data being harvested by data controllers
makes it increasingly necessary to use the cloud not just to store the data, but also to …

Abstract Machine learning (ML) and Deep learning (DL) models are popular in many areas,
from business, medicine, industries, healthcare, transportation, smart cities, and many more …

Privacy and data protection constitute core values of individuals and of democratic societies.
There have been decades of debate on how those values-and legal obligations-can be …

Because privacy concerns in IoT devices are the most sensitive of all the difficulties, such an
extreme growth in IoT usage has an impact on the privacy and life spans of IoT devices …

Mobile devices equipped with rich sensors, such as smartphones, watches, or vehicles,
have been pervasively used all around the world. Their high penetration and powerful …

Abstract The dissemination of Electronic Health Records (EHRs) can be highly beneficial for
a range of medical studies, spanning from clinical trials to epidemic control studies, but it …

Trajectory datasets are becoming more and more popular due to the massive usage of GPS
and other location-based devices and services. In this paper, we address privacy issues …

Mining health data can lead to faster medical decisions, improvement in the quality of
treatment, disease prevention, and reduced cost, and it drives innovative solutions within the …

It is not uncommon in the data anonymization literature to oppose the “old” k k-anonymity
model to the “new” differential privacy model, which offers more robust privacy guarantees …

The extensive collection and processing of personal information in big data analytics has
given rise to serious privacy concerns, related to wide scale electronic surveillance, profiling …