Event processing (EP) is a data processing technology that conducts online processing of
event information. In this survey, we summarize the latest cutting-edge work done on EP …

In this paper, we present a comprehensive survey of privacy-preserving schemes for smart
grid communications. Specifically, we select and in-detail examine thirty-two privacy …

Federated learning (FL) is a machine learning setting where many clients (eg, mobile
devices or whole organizations) collaboratively train a model under the orchestration of a …

By leveraging deep learning-based technologies, industrial artificial intelligence (IAI) has
been applied to solve various industrial challenging problems in Industry 4.0. However, for …

Federated learning facilitates the collaborative training of models without the sharing of raw
data. However, recent attacks demonstrate that simply maintaining data locality during …

We design a novel, communication-efficient, failure-robust protocol for secure aggregation of
high-dimensional data. Our protocol allows a server to compute the sum of large, user-held …

We consider the problem of designing scalable, robust protocols for computing statistics
about sensitive data. Specifically, we look at how best to design differentially private …

Fog computing-enhanced Internet of Things (IoT) has recently received considerable
attention, as the fog devices deployed at the network edge can not only provide low latency …

This paper introduces Flamingo, a system for secure aggregation of data across a large set
of clients. In secure aggregation, a server sums up the private inputs of clients and obtains …

Machine learning (ML) has been widely recognized as an enabler of the global trend of
digital transformation. With the increasing adoption of data-hungry machine learning …