Abstract Machine Learning (ML) models are ubiquitous in real-world applications and are a
constant focus of research. Modern ML models have become more complex, deeper, and …

Deep learning is one of the advanced approaches of machine learning, and has attracted a
growing attention in the recent years. It is used nowadays in different domains and …

Deep Learning (DL) algorithms based on artificial neural networks have achieved
remarkable success and are being extensively applied in a variety of application domains …

Differential privacy is a strong notion for privacy that can be used to prove formal
guarantees, in terms of a privacy budget, ε, about how much information is leaked by a …

Generative Adversarial Network (GAN) and its variants have recently attracted intensive
research interests due to their elegant theoretical foundation and excellent empirical …

By learning generative models of semantic-rich data distributions from samples, generative
adversarial network (GAN) has recently attracted intensive research interests due to its …

The ever-growing advances of deep learning in many areas including vision,
recommendation systems, natural language processing, etc., have led to the adoption of …

Recent years have witnessed remarkable successes of machine learning in various
applications. However, machine learning models suffer from a potential risk of leaking …

Over the past few years, providers such as Google, Microsoft, and Amazon have started to
provide customers with access to software interfaces allowing them to easily embed …

This paper aims to develop a new efficient framework named Secure Decentralized Training
Framework (SDTF) for Privacy Preserving Deep Learning models. The main feature of the …