Artificial intelligence has made remarkable progress in handling complex tasks, thanks to
advances in hardware acceleration and machine learning algorithms. However, to acquire …

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) …

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 …

Nowadays, cloud computing has developed well and been applied in many kinds of areas.
However, privacy is still the most challenging problem which obstructs it being applied in …

Recent advances in sensing and storing technologies have led to big data age where a
huge amount of data are distributed across sites to be stored and analysed. Indeed, cluster …

Today, more and more data is collected and stored by different organizations. When the data
is distributed among multiple users who wish to perform data mining on the joint data …

Privacy-preserving machine learning has become an important study at present due to
privacy policies. However, the efficiency gap between the plain-text algorithm and its privacy …

In many industrial Internet of Things application schemes, participants, such as IoT devices,
often share information with each others for analysis and categorization purpose. Through …

As a commonly used algorithm in data mining, clustering has been widely applied in many
fields, such as machine learning, information retrieval, and pattern recognition. In reality …

In this paper we provide a fully distributed implementation of the k-means clustering
algorithm, intended for wireless sensor networks where each agent is endowed with a …