The vulnerabilities of machine learning models open the door for deceit, giving malicious operators the opportunity to interfere with the calculations or decision making of machine learning systems.
Domain adaptation remains a significant challenge in artificial intelligence, especially when models trained in one domain are required to perform ...
NIST’s National Cybersecurity Center of Excellence (NCCoE) has released a draft report on machine learning (ML) for public comment. A Taxonomy and Terminology of Adversarial Machine Learning (Draft ...
Intrusion detection systems, long constrained by high false-positive rates and limited adaptability, are being re-engineered ...
Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in image-related tasks. These ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More With 77% of enterprises already victimized by adversarial AI attacks and ...
Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial ...
Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. It is widely accepted sage wisdom to garner as much as you can ...
HOUSTON – (Sept. 3, 2025) – Quantum computers promise enormous computational power, but the nature of quantum states makes computation and data inherently “noisy.” Rice University computer scientists ...
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