Anonymization techniques are widely used to make personal data broadly available for
analytics/data-mining purposes while preserving the privacy of the personal information …

Smart cities, leveraging IoT technologies, are revolutionizing the quality of life for citizens.
However, the massive data generated in these cities also poses significant privacy risks …

Digital health data collection is vital for healthcare and medical research. But it contains
sensitive information about patients, which makes it challenging. To collect health data …

The smart grid (SG) is a new type of grid that integrates traditional power grid with the
Internet of Things (IoT) to make the entire grid system more compatible, controllable, and self …

With the development of IoT technology, personal data are being collected in many places.
These data can be used to create new services, but consideration must be given to the …

Federated learning (FL) has emerged as a promising solution to address the challenges
posed by data silos and the need for global data fusion. It offers a distributed machine …

Location-based services have become an important part of our daily lives, and while users
enjoy convenient Internet services, they also face the risk of privacy leakage. K-anonymity is …

Federated learning has gained considerable attention as the solution for handling
distributed and privacy-sensitive data. This includes scenarios such as predicting …

Currently, many global organizations collect personal data for marketing, recommendation
system improvement, and other purposes. Some organizations collect personal data …

The collection of medical data and personal health data is taking place in diverse locations
due to the development of IoT technology. This has created possibilities for using medical …