The rapid advances in the Internet of Things (IoT) have promoted a revolution in
communication technology and offered various customer services. Artificial intelligence (AI) …

This article provides a comprehensive overview of the fairness issues in artificial intelligence
(AI) systems, delving into its background, definition, and development process. The article …

Secure two-party neural network inference (2PC-NN) can offer privacy protection for both the
client and the server and is a promising technique in the machine-learning-as-a-service …

Secure multi-party computation (MPC) allows parties to perform computations on data while
kee** that data private. This capability has great potential for machine-learning …

The wide adoption of Machine Learning to solve a large set of real-life problems came with
the need to collect and process large volumes of data, some of which are considered …

As data privacy increasingly becomes a critical societal concern, federated learning has
been a hot research topic in enabling the collaborative training of machine learning models …

Deep learning is currently widely used in a variety of applications, including computer vision
and natural language processing. End devices, such as smartphones and Internet-of-Things …

Today's artificial intelligence still faces two major challenges. One is that, in most industries,
data exists in the form of isolated islands. The other is the strengthening of data privacy and …

Many companies provide neural network prediction services to users for a wide range of
applications. However, current prediction systems compromise one party's privacy: either the …

As machine learning becomes more widely used, the need to study its implications in
security and privacy becomes more urgent. Although the body of work in privacy has been …