With the advent of functional encryption (FE), new possibilities for the computation of
encrypted data have arisen. FE enables data owners to grant third-party access to perform …

Deep learning (DL) has demonstrated superior success in various of applications, such as
image classification, speech recognition, and anomalous detection. The unprecedented …

Abstract Knowledge Graph (KG) has attracted more and more companies' attention for its
ability to connect different types of data in meaningful ways and support rich data services …

Cloud-edge collaborative learning has received considerable attention recently, which is an
emerging distributed machine learning (ML) architecture for improving the performance of …

Machine learning has become ubiquitous technology and is being used in many aspects of
our daily lives. However, as machine learning works with a huge amount of data, many …

Homomorphic encryption (HE) allows computing encrypted data in the ciphertext domain
without knowing the encryption key. It is possible, however, to break fully homomorphic …

This paper demonstrates the first side-channel attack on homomorphic encryption (HE),
which allows computing on encrypted data. We reveal a power-based side-channel leakage …

In today's machine learning landscape, fine-tuning pretrained transformer models has
emerged as an essential technique, particularly in scenarios where access to task-aligned …

Adopting cryptography has given rise to a significant? evolution in AI. This chapter studies
the path and stages of this evolution. We start with reviewing existing relevant surveys …

The advances in machine learning technology has promoted its great potential for deep
neural network (DNN) inference powered applications of Internet of Things (IoT), such as …