With the continuous promotion and deepened application of Machine Learning-as-a-Service
(MLaaS) across various societal domains, its privacy problems occur frequently and receive …

In recent years, there have been many cloud-based machine learning services, where well-
trained models are provided to users on a pay-per-query scheme through a prediction API …

The exponential growth of big data and deep learning has increased the data exchange
traffic in society. Machine Learning as a Service,(MLaaS) which leverages deep learning …

Public intelligent services enabled by machine learning algorithms are vulnerable to model
extraction attacks that can steal confidential information of the learning models through …

Privacy preserving in machine learning is a crucial issue in industry informatics since data
used for training in industries usually contain sensitive information. Existing differentially …

Machine learning service API allows model owners to monetize proprietary models by
offering prediction services to third-party users. However, existing literature shows that …

Privacy-preserving data publishing has been an important research field in the era of big
data. Various privacy protection schemes have been proposed to balance privacy and utility …

In the recent decade, deep learning techniques have been widely adopted for founding
artificial Intelligent applications, which led to successes in many data analysis tasks, such as …

Massive volumes of sensitive information are being collected for data analytics and machine
learning, such as large scale Internet of Things (IoT) data. Some IoT data contain users' …

Users usually have different privacy demands when they contribute individual data to a
dataset that is maintained and queried by others. To tackle this problem, several …