Decentralized paradigm in the field of cybersecurity and machine learning (ML) for the
emerging Internet of Things (IoT) has gained a lot of attention from the government …

With rapid development of enabling technologies such as Internet of Things, robotics, and
big data, the fourth industrial revolution known as “Industry 4.0”(I4. 0) has become a great …

摘要传统的数据库管理系统主要由单一机构管理和维护, 在多方参与者协作的场景中,
因无法完全信任数据库中的数据, 每方都需要单独构建一套承载自己业务数据的数据库 …

Blockchain is a technology that has desirable features of decentralization, autonomy,
integrity, immutability, verification, fault-tolerance, anonymity, auditability, and transparency …

Trust, traceability, and transparency emerge as critical factors in designing circular
blockchain platforms in supply chains. To bridge the three circular supply chain reverse …

Envisioned to be the next-generation Internet, the metaverse has been attracting enormous
attention from both the academia and industry. The metaverse can be viewed as a 3D …

Membership inference is one of the simplest privacy threats faced by machine learning
models that are trained on private sensitive data. In this attack, an adversary infers whether a …

Federated learning (FL) is a machine learning setting where many clients (eg, mobile
devices or whole organizations) collaboratively train a model under the orchestration of a …

When talking about blockchain technology in academia, business, and society, frequently
generalizations are still heared about its–supposedly inherent–enormous energy …

In federated learning, multiple client devices jointly learn a machine learning model: each
client device maintains a local model for its local training dataset, while a master device …