Machine-Learning-as-a-Service (MLaaS) has become a widespread paradigm, making
even the most complex Machine Learning models available for clients via, eg, a pay-per …

Future connected and autonomous vehicles (CAVs) must be secured against cyberattacks
for their everyday functions on the road so that safety of passengers and vehicles can be …

In a model extraction attack, an adversary steals a copy of a remotely deployed machine
learning model, given oracle prediction access. We taxonomize model extraction attacks …

Machine learning involves expensive data collection and training procedures. Model owners
may be concerned that valuable intellectual property can be leaked if adversaries mount …

With wide deployment of machine learning (ML)-based systems for a variety of applications
including medical, military, automotive, genomic, multimedia, and social networking, there is …

Nowadays, due to the breakthrough in natural language generation (NLG), including
machine translation, document summarization, image captioning, etc NLG models have …

High-performance Deep Neural Networks (DNNs) are increasingly deployed in many real-
world applications eg, cloud prediction APIs. Recent advances in model functionality …

Training machine learning (ML) models typically involves expensive iterative optimization.
Once the model's final parameters are released, there is currently no mechanism for the …

Machine learning is being increasingly used by individuals, research institutions, and
corporations. This has resulted in the surge of Machine Learning-as-a-Service (MLaaS) …

Adversaries may look to steal or attack black-box NLP systems, either for financial gain or to
exploit model errors. One setting of particular interest is machine translation (MT), where …