With the growing significance of Credit Risk Analysis (CRA) with a focus on privacy, there is
a pressing demand for a Privacy Preserving Machine Learning (PPML) decision support …

Logistic regression is a data statistical technique, which is used to predict the probability that
an event occurs. For some scenarios where the storage capabilities and computing …

In the era of big data, data are often outsourced at cloud for storage and computation. As
data has become a highly valuable resource, data holder needs retain full privacy and …

Homomorphic encryption (HE) is one of promising cryptographic candidates resolving
privacy issues in machine learning on sensitive data such as biomedical data and financial …

The protection of data processing is emerging as an essential aspect of data analytics,
machine learning, delegation of computation, Internet of Things, medical and financial …

Homomorphic encryption (HE) has recently attracted considerable attention as a key
solution for privacy-preserving machine learning because HE can apply to various areas …

Logistic regression is a powerful machine learning tool to classify data. When dealing with
sensitive or private data, cares are necessary. In this paper, we propose a secure system for …

Abstract Machine Learning as a Service (MLaaS) is a robust platform that offers various
emerging applications. Despite great convenience, user privacy has become a paramount …

Machine Learning as a Service (MLaaS) has accelerated the adoption of machine learning
techniques in various domains. However, this trend has also raised serious concerns over …

Privacy in machine learning has been widely recognized as an essential ethical and legal
issue, because the data used for machine learning may contain sensitive information …