The rapid development of Artificial Intelligence (AI) technology has enabled the deployment
of various systems based on it. However, many current AI systems are found vulnerable to …

The development of Internet of Things (IoT) brings new changes to various fields.
Particularly, industrial IoT (IIoT) is promoting a new round of industrial revolution. With more …

Logs are widely used in system management for dependability assurance because they are
often the only data available that record detailed system runtime behaviors in production …

With the deep penetration of the Internet and mobile devices, privacy preservation in the
local setting has become increasingly relevant. The local setting refers to the scenario where …

Online evaluation is one of the most common approaches to measure the effectiveness of an
information retrieval system. It involves fielding the information retrieval system to real users …

With the popularity of smart devices and the widespread use of machine learning methods,
smart edges have become the mainstream of dealing with wireless big data. When smart …

Corporations, organizations, and governments have collected, digitized, and stored
information in digital forms since the invention of computers, and the speed of such data …

Streaming data, crucial for applications like crowd-sourcing analytics, behavior studies, and
real-time monitoring, faces significant privacy risks due to the large and diverse data linked …

The smart grid frequently collects consumers' fine-grained power usage data through smart
meters to facilitate various applications, such as billing, load monitoring, regional statistics …

Differentially private federated learning (DP-FL) is a promising technique for collaborative
model training while ensuring provable privacy for clients. However, optimizing the tradeoff …