With the implementation of privacy protection laws such as GDPR, it is increasingly difficult
for organizations to legally collect users' data. However, a typical machine learning-based …

Tensors are popular and versatile tools which model multidimensional data. Tensor
decomposition has emerged as a powerful technique dealing with multidimensional data …

Secure outsourced computation is a key technique for protecting data security and privacy in
the cloud. Although fully homomorphic encryption (FHE) enables computations over …

Evolutionary algorithms (EAs), such as the genetic algorithm (GA), offer an elegant way to
handle combinatorial optimization problems (COPs). However, limited by expertise and …

In traditional recommender systems, we often build models based on a centralized storage
of user data, which however will lead to user privacy concerns and risks. In this paper, we …

One existing challenge associated with large scale skyline queries on cloud services,
particularly when dealing with private information such as biomedical data, is supporting …

Outsourcing data and computation to cloud server provides a cost-e ective way to support
large scale data storage and query processing. However, due to security and privacy …

Classification of personal text messages has many useful applications in surveillance, e-
commerce, and mental health care, to name a few. Giving applications access to personal …

As an essential technology underpinning trusted computing, the trusted execution
environment (TEE) allows one to launch computation tasks on both on-and off-premises …

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 …