The rapid-developing Artificial Intelligence (AI) technology, fast-growing network traffic, and
emerging intelligent applications (eg, autonomous driving, virtual reality, etc.) urgently …

Recent advances in hardware and information technology have accelerated the proliferation
of smart and interconnected devices facilitating the rapid development of the Internet of …

Data privacy concerns are increasing significantly in the context of the Internet of Things,
cloud services, edge computing, artificial intelligence applications, and other applications …

Machine learning (ML) techniques have been widely used in many smart city sectors, where
a huge amount of data is gathered from various (IoT) devices. As a typical ML model …

We present Chameleon, a novel hybrid (mixed-protocol) framework for secure function
evaluation (SFE) which enables two parties to jointly compute a function without disclosing …

Federated learning can combine a large number of scattered user groups and train models
collaboratively without uploading data sets, so as to avoid the server collecting user …

Complex machine learning (ML) inference algorithms like recurrent neural networks (RNNs)
use standard functions from math libraries like exponentiation, sigmoid, tanh, and reciprocal …

Online fault detection is one of the key technologies to improve the performance of cloud
systems. The current data of cloud systems is to be monitored, collected and used to reflect …

In recent years, more and more machine learning algorithms depend on the cloud
computing. When a machine learning system is trained or classified in the cloud …

This paper introduces an accurate and robust facial expression recognition (FER) system.
For feature extraction, the proposed FER system employs stepwise linear discriminant …