Given its advantages in low latency, fast response, context-aware services, mobility, and
privacy preservation, edge computing has emerged as the key support for intelligent …

Fast-growing smart city applications, such as smart delivery, smart community, and smart
health, are generating big data that are widely distributed on the internet. IoT (Internet of …

The confidential data is mainly managed by creating passwords, tokens, and unique
identifiers in an authorized manner. These records must be kept in a safe location away from …

The massive upsurge in computational and storage has driven the local data and machine
learning applications to the cloud environment. The owners may not fully trust the cloud …

The security of Internet communications has traditionally been delegated to controls at lower
layers of the Transmission Control Protocol/Internet Protocol (TCP/IP) architecture. However …

Millions of users across the world leverages data processing and sharing benefits from
cloud environment. Data security and privacy are inevitable requirement of cloud …

The increased usage of IoT networks brings about new privacy risks, especially when
intrusion detection systems (IDSs) rely on large datasets for machine learning (ML) tasks …

Abstract Mobile Edge Computing (MEC) is a modern paradigm that involves moving
computing and storage resources closer to the network edge, reducing latency, and …

Location‐based services (LBS) have become an important research area with the rapid
development of mobile Internet technology, GPS positioning technology, and the …

Existing research in differential privacy, whose applications have exploded across functional
areas in the last few years, describes an intrinsic trade-off between the privacy of a dataset …