The rapidly growing scale and variety of biomedical data repositories raise important privacy
concerns. Conventional frameworks for collecting and sharing human subject data offer …

Secure multi-party computation (MPC) is an essential tool for privacy-preserving machine
learning (ML). However, secure training of large-scale ML models currently requires a …

Machine learning algorithms crucially depend on non-linear mathematical functions such as
division (for normalization), exponentiation (for softmax and sigmoid), tanh (as an activation …

Inventory matching is a standard mechanism for trading financial stocks by which buyers
and sellers can be paired. In the financial world, banks often undertake the task of finding …

Secure multiparty computation (MPC) enables privacy-preserving collaborative computation
over sensitive data held by multiple mutually distrusting parties. Unfortunately, in the most …

A threshold signature scheme distributes the ability to generate signatures through
distributed key generation and signing protocols. A threshold signature scheme should be …

Blockchain is a newly emerging technology, however, it has proven effective in many
applications because it provides multiple advantages, mainly as it represents a trust system …

Private heavy-hitters is a data-collection task where multiple clients possess private bit
strings, and data-collection servers aim to identify the most popular strings without learning …

Intellectual Property (IP) thefts of trained machine learning (ML) models through side-
channel attacks on inference engines are becoming a major threat. Indeed, several recent …

Artificial intelligence (AI) has helped industries and society today to become modern and
more productive. Using the Internet of Things (IoT), we can sense and transfer data through …