However, the security vulnerabilities ... used for modern AI development (Linux, BERT, PyTorch, and Transformers), as well as the AI repositories that utilize foundation repositories as dependencies.

Abstract: With the booming development of deep learning and machine learning, the use of neural networks for software source code security vulnerability detection has become a hot pot in the field of ...

He solidified his credentials by gaining in-depth knowledge of critical technologies, including AI-driven cloud computing, machine learning ... the development process and enforce security ...

and the systems that host them need to have strong security protections and policies in place. A recent vulnerability patched in MLflow, an open-source machine-learning lifecycle platform ...

This repository contains the dataset and model used in the publications Machine learning on knowledge graphs for context-aware security monitoring (IEEE CSR 2021) and An energy-based model for ...

At the endless booths of this week's RSA security trade show in ... for mentions of software security vulnerabilities, and then, using their machine-learning-trained algorithm, assessed how ...

Microsoft Corp. today announced a new method for discovering software security vulnerabilities that combines machine learning and ... efficient and generic,” Development Lead William Blum ...

As someone who's been following the intersection of technology and security, I'm fascinated by how machine learning (ML ... is also being used to identify vulnerabilities in existing encryption ...

What is this book about? Graph Machine Learning provides a new set of tools for processing network data and leveraging the power of the relation between entities that can be used for predictive, ...