ReLUSyn: Synthesizing stealthy attacks for deep neural network-based safety-critical cyber-physical systems
Aarti Kashyap · 2020
Safety-critical cyber-physical systems have become an important part of our society. The controllers for safety-critical systems have recently been leveraging the research progress in Deep Neural Networks (DNNs) in order to construct data-driven models with high safety and reliability properties. There have been multiple approaches that are being used to enforce properties such as safety and stability on the models obtained after training in order to obtain robust neural networks.