Secure computation enables mutually distrusting parties to jointly evaluate a function on
their private inputs without revealing anything but the function's output. Generic secure …

Abstract Internet of Things (IoT) is going to create a world where physical objects are
seamlessly integrated into information networks in order to provide advanced and intelligent …

Secure multi-party computation (MPC) allows a group of mutually distrustful parties to
compute a joint function on their inputs without revealing any information beyond the result …

Nowadays an emerging class of applications are based oncollaboration over a shared
database among different entities. However, the existing solutions on shared database may …

In recent years, signal processing applications that deal with user-related data have aroused
privacy concerns. For instance, face recognition and personalized recommendations rely on …

Recommender systems have become an important tool for personalization of online
services. Generating recommendations in online services depends on privacy-sensitive data …

Secure computation is a promising approach to business problems in which several parties
want to run a joint application and cannot reveal their inputs. Secure computation preserves …

Recent advances in biometric recognition and the increasing use of biometric data prompt
significant privacy challenges associated with the possible misuse, loss, or theft of biometric …

Data mining has emerged as a significant technology for gaining knowledge from vast
quantities of data. However, there has been growing concern that use of this technology is …

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