The shift towards efficient and automated data analysis through Machine Learning (ML) has
notably impacted healthcare systems, particularly Radiomics. Radiomics leverages ML to …

In the era of Big Data and Artificial Intelligence (AI), the unprecedented scale and complexity
of data collection, processing, and analysis pose significant privacy challenges. This paper …

Delegation learning is indeed a prevalent approach in privacy-preserving machine learning
(PPML), especially when dealing with big data. It specifically involves data owners …

Generative artificial intelligence has made great progress in enabling clients to create a
variety of realistic visual content (such as images, videos and audios), where diffusion model …

The field of verifiable secret sharing schemes was introduced by Verheul et al. and has
evolved over time, including well-known examples by Feldman and Pedersen. Stinson …

Abstract Machine learning applications gain more and more access to highly sensitive
information while simultaneously requiring more and more computation resources. Hence …

A smart grid is a contemporary electrical system that supports two-way communication and
utilizes the concept of demand response. In order to increase the smart grid's dependability …

The integration of machine learning (ML) into various domains has raised significant
concerns regarding the privacy of individuals. As datasets grow larger and more complex …

Intrusion Detection Systems (IDS) are the key for securing the rapidly evolving Internet-of-
Things (IoT), where data security and privacy will become increasingly important in the …

A Aprendizagem Máquina (AM) tornou–se uma técnica essencial para vários sectores (p.
ex., saúde, finanças) que pretendem extrair novas informações dos seus dados. No entanto …