Cloud computing and cloud storage have contributed to a big shift in data processing and its
use. Availability and accessibility of resources with the reduction of substantial work is one of …

Legacy encryption systems depend on sharing a key (public or private) among the peers
involved in exchanging an encrypted message. However, this approach poses privacy …

Contact tracing is an essential tool for public health officials and local communities to fight
the spread of novel diseases, such as for the COVID-19 pandemic. The Singaporean …

With the advance of machine learning and the Internet of Things (IoT), security and privacy
have become critical concerns in mobile services and networks. Transferring data to a …

Secure aggregation is a cryptographic primitive that enables a server to learn the sum of the
vector inputs of many clients. Bonawitz et al.(CCS 2017) presented a construction that incurs …

Data privacy concerns are increasing significantly in the context of the Internet of Things,
cloud services, edge computing, artificial intelligence applications, and other applications …

Deep Learning (DL) algorithms based on artificial neural networks have achieved
remarkable success and are being extensively applied in a variety of application domains …

Secure multi-party computation (MPC) has evolved from a theoretical curiosity in the 1980s
to a tool for building real systems today. Over the past decade, MPC has been one of the …

Due to the strong analytical ability of big data, deep learning has been widely applied to
model on the collected data in industrial Internet of Things (IoT). However, for privacy issues …

We suggest a method to construct a homomorphic encryption scheme for approximate
arithmetic. It supports an approximate addition and multiplication of encrypted messages …