As machine learning becomes more widely used, the need to study its implications in
security and privacy becomes more urgent. Although the body of work in privacy has been …

Artificial intelligence (AI) has achieved remarkable breakthroughs in a wide range of fields,
ranging from speech processing, image classification to drug discovery. This is driven by the …

The computation for today's intelligent personal assistants such as Apple Siri, Google Now,
and Microsoft Cortana, is performed in the cloud. This cloud-only approach requires …

The prevalence of deep learning has drawn attention to the privacy protection of sensitive
data. Various privacy threats have been presented, where an adversary can steal model …

Although Deep Neural Networks (DNN) are ubiquitously utilized in many applications, it is
generally difficult to deploy DNNs on resource-constrained devices, eg, mobile platforms …

Despite the evolution and enhancements that mobile devices have experienced, they are
still considered as limited computing devices. Today, users become more demanding and …

As user demand scales for intelligent personal assistants (IPAs) such as Apple's Siri,
Google's Google Now, and Microsoft's Cortana, we are approaching the computational limits …

Benefiting from the advance of deep learning (DL) technology, Internet-of-Things (IoT)
devices and systems are becoming more intelligent and multifunctional. They are expected …

Recent years have witnessed a rapid growth of deep-network based services and
applications. A practical and critical problem thus has emerged: how to effectively deploy the …

With the vigorous development of artificial intelligence (AI), intelligence applications based
on deep neural networks (DNNs) have changed people's lifestyles and production …