Over the course of the last twenty years, research in data mining has seen a substantial
increase in interest, attracting original contributions from various disciplines including …

With the development of information science and modern technology, it becomes more
important about how to protect privacy information. In this paper, a novel privacy-preserving …

A proxy blind signature allows the designated proxy signer using the proxy private key to
generate a blind signature on behalf of the original signer. In previous proxy blind signature …

We propose a privacy-preserving support vector machine (SVM) classifier for a data matrix A
whose input feature columns as well as individual data point rows are divided into groups …

Elastic net is a popular linear regression tool and has many important applications, in
particular, finding genomic biomarkers for cancers from gene expression profiles for …

Privacy concern has been increasingly important in many machine learning (ML) problems.
We study empirical risk minimization (ERM) problems under secure multi-party computation …

In recent years, the social security problems are becoming more and more complex, and the
public security work is arduous. The traditional governance mode needs more …

The collection and exploration of a profusion of location data for mobility pattern mining has
been met with stiff resistance from individuals and privacy groups due to privacy and security …

Abstract Machine learning, especially deep learning, is a hot research field in academia,
and it is revolutionizing industry. However, the privacy-preserving problems are not solved …

Privacy-preserving data mining (PPDM) is a recent emergent research area that deals with
the incorporation of privacy preserving concerns to data mining techniques. We consider a …