In recent years, privacy-preserving data mining has been studied extensively, because of
the wide proliferation of sensitive information on the internet. A number of algorithmic …

In the era of “big data,” a huge number of people, devices, and sensors are connected via
digital networks and the cross‐plays among these entities generate enormous valuable data …

The ever-growing demand for electrical energy of sensing devices in the Internet of Things
(IoT) has led to generating large amounts of electricity consumption data. Electricity service …

Cloud computing empowers enterprises to efficiently manage big data and discovery of
useful information which are the most fundamental challenges for big data enabled …

Gaining access to high-quality data is a vital necessity in knowledge-based decision
making. But data in its raw form often contains sensitive information about individuals …

In this paper, we consider the problem of mutual privacy protection in social participatory
sensing in which individuals contribute their private information to build a (virtual) …

Privacy preserving data classification is an important research area in data mining field. The
goal of a privacy preserving classification algorithm is to protect the sensitive information as …

Clustering is a popular unsupervised machine learning technique that groups similar input
elements into clusters. It is used in many areas ranging from business analysis to health …

The process of record linkage seeks to integrate instances that correspond to the same
entity. Record linkage has traditionally been performed through the comparison of …

Clustering technique plays a critical role in data mining, and has received great success to
solve application problems like community analysis, image retrieval, personalized …