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 …

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 …

The advent of the Internet of Things (IoT) has brought forth an era of unprecedented
connectivity, with an estimated 80 billion smart devices expected to be in operation by the …

Most current approaches for protecting privacy in machine learning (ML) assume that
models exist in a vacuum. Yet, in reality, these models are part of larger systems that include …

Deep Neural Networks (DNNs) are fast becoming ubiquitous for their ability to attain good
accuracy in various machine learning tasks. A DNN's architecture (ie, its hyperparameters) …

Deep learning is gaining importance in many applications. However, Neural Networks face
several security and privacy threats. This is particularly significant in the scenario where …

Neural Network (NN) accelerators are currently widely deployed in various security-crucial
scenarios, including image recognition, natural language processing and autonomous …

Machine learning has been attracting strong interests in recent years. Numerous companies
have invested great efforts and resources to develop customized deep-learning models …

Deep Neural Network (DNN) models have been extensively developed by companies for a
wide range of applications. The development of a customized DNN model with great …

Rowhammer Attack, a new DRAM-based attack, was developed exploiting weak cells to
alter their content. Such attacks can be launched at the user level without requiring access …