Large language models (LLMs) have demonstrated extraordinary capabilities and
contributed to multiple fields, such as generating and summarizing text, language …

This paper presents a comprehensive survey of existing authentication and privacy-
preserving schemes for 4G and 5G cellular networks. We start by providing an overview of …

Machine learning (ML) has become a core component of many real-world applications and
training data is a key factor that drives current progress. This huge success has led Internet …

Secure Multi-party Computation (MPC) allows a set of mutually distrusting parties to jointly
evaluate a function on their private inputs while maintaining input privacy. In this work, we …

Facial recognition technology (FRT) has emerged as a powerful tool for public governance
and security, but its rapid adoption has also raised significant concerns about privacy, civil …

With the rapid development of artificial intelligence (AI), AI anxiety has emerged and is
receiving widespread attention, but research on this topic is not comprehensive. Therefore …

We present Chameleon, a novel hybrid (mixed-protocol) framework for secure function
evaluation (SFE) which enables two parties to jointly compute a function without disclosing …

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 Machine learning classification is used in numerous settings nowadays, such as
medical or genomics predictions, spam detection, face recognition, and financial predictions …

Classifier has been widely applied in machine learning, such as pattern recognition, medical
diagnosis, credit scoring, banking and weather prediction. Because of the limited local …