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

Machine learning (ML) and artificial intelligence (AI) are essential components in modern and effective cybersecurity solutions. However, as the use of ML and AI in cybersecurity is increasingly ...

The Artificial Intelligence and Machine Learning (“AI/ML”) risk environment is in flux. One reason is that regulators are shifting from AI safety to AI innovation approaches, as a recent DataPhiles ...

The integration of deep learning techniques into wireless communication systems has catalysed notable advancements in tasks such as modulation classification and spectrum sensing. However, the ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Security leaders’ intentions aren’t matching up with their actions to ...

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 ...

AI-driven attacks leaked 23.77 million secrets in 2024, revealing that NIST, ISO, and CIS frameworks lack coverage for ...

Artificial intelligence (AI) safety has turned into a constant cat-and-mouse game. As developers add guardrails to block ...

In a landmark move, the US National Institute of Standards and Technology (NIST) has taken a new step in developing strategies to fight against cyber-threats that target AI-powered chatbots and ...

With the EU's AI Act coming into force imminently, those designing, developing, and/or deploying AI will need to start getting to grips with the myriad of new obligations, including new cyber security ...

Perspecta Labs has been awarded the Autonomous Defensive Cyber Operations program from the U.S. Army Combat Capabilities Development Command (CCDC), Command, Control, Computers, Communications, Cyber, ...