The study, titled Conditional Adversarial Fragility in Financial Machine Learning under Macroeconomic Stress, published as a ...

Machine learning (ML) has recently been applied for the classification of radio frequency (RF) signals. One use case of interest relates to the discernment between different wireless protocols that ...

As AI applications and capabilities continue to progress rapidly, so do efforts into exploiting its vulnerabilities, mainly through the Adversarial AI research field. As these trends persist, AI ...

Machines' ability to learn by processing data gleaned from sensors underlies automated vehicles, medical devices and a host of other emerging technologies. But that learning ability leaves systems ...

Microsoft and MITRE have developed a plug-in that combines several open-source software tools to help cybersecurity professionals better prepare for attacks on machine learning (ML) systems. “Bringing ...

The National Institute of Standards and Technology (NIST) has published its final report on adversarial machine learning (AML), offering a comprehensive taxonomy and shared terminology to help ...