Over the past years, the increasingly severe data island problem has spawned an emerging
distributed deep learning framework—federated learning, in which the global model can be …

Applications today rely on cloud databases for storing and querying time-series data. While
outsourcing storage is convenient, this data is often sensitive, making data breaches a …

The mode is a fundamental descriptive statistic in data analysis, signifying the most frequent
element within a dataset. The range mode query (RMQ) problem expands upon this concept …

The sixth-generation (6G) communication technology has been attracting great interests
from both industry and academia, as it is regarded as a promising approach to achieve more …

With the rapid development of cloud computing, massive amounts of data are uploaded to
cloud servers for storage. For privacy protection, sensitive data should be encrypted before …

It is undeniable that Internet of Things (IoT) in big data era can provide us with huge volumes
of multi-dimensional data, transforming our society into a much more intelligent one. In order …

The advance of cloud computing has driven a new paradigm of outsourcing large-scale data
and data-driven services to public clouds. Due to the increased awareness of privacy …

Similarity queries, giving a way to disease diagnosis based on similar patients, have wide
applications in eHealthcare and are essentially demanded to be processed under fine …

As a popular and practical query type in location-based services, the spatial keyword query
has been extensively studied in both academia and industry. Meanwhile, with the growing …

Wireless body area network (WBAN) and big data techniques indubitably enable the online
medical diagnosis system to be more practical. In the system, to make a more accurate …