With the proliferation of Beyond 5G (B5G) communication systems and heterogeneous
networks, mobile broadband users are generating massive volumes of data that undergo …

Abstract The Internet of Things (IoT) refers to a network of Internet-enabled devices that can
make different operations, like sensing, communicating, and reacting to changes arising in …

As mobile devices continuously generate streams of images and videos, a new class of
mobile deep vision applications are rapidly emerging, which usually involve running deep …

The exponential growth of data generated from increasing smart meters and smart
appliances brings about huge potentials for more efficient energy production, pricing, and …

Federated learning has attracted much research attention due to its privacy protection in
distributed machine learning. However, existing work of federated learning mainly focuses …

On-device learning is a promising technique for emerging privacy-preserving machine
learning paradigms. However, through quantitative experiments, we find that commodity …

Deep learning models are increasingly used in mobile applications as critical components.
Unlike the program bytecode whose vulnerabilities and threats have been widely-discussed …

On-device ML introduces new security challenges: DNN models become white-box
accessible to device users. Based on white-box information, adversaries can conduct …

Privacy and security-related concerns are growing as machine learning reaches diverse
application domains. The data holders want to train or infer with private data while exploiting …