The past four years have witnessed the rapid development of federated learning (FL).
However, new privacy concerns have also emerged during the aggregation of the …

Huge amounts of unstructured data including image, video, audio, and text are ubiquitously
generated and shared, and it is a challenge to protect sensitive personal information in …

Federated learning involves training statistical models over remote devices or siloed data
centers, such as mobile phones or hospitals, while keeping data localized. Training in …

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 …

Anonymization is a practical solution for preserving user's privacy in data publishing. Data
owners such as hospitals, banks, social network (SN) service providers, and insurance …

Many modern cities strive to integrate information technology into every aspect of city life to
create so-called smart cities. Smart cities rely on a large number of application areas and …

Artificial Intelligence (AI) has attracted a great deal of attention in recent years. However,
alongside all its advancements, problems have also emerged, such as privacy violations …

Local Energy Communities (LECs) can facilitate the transition towards sustainable and
clean energy system infrastructure. In this work, we construct a novel hierarchical energy …

Position-based services (PBSs) that deliver networked amenities based on roaming user's
positions have become progressively popular with the propagation of smart mobile devices …

Security metrics have received significant attention. However, they have not been
systematically explored based on the understanding of attack-defense interactions, which …