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.

The final guidance for defending against adversarial machine learning offers specific solutions for different attacks, but warns current mitigation is still developing. NIST Cyber Defense The final ...

Imagine the following scenarios: An explosive device, an enemy fighter jet and a group of rebels are misidentified as a cardboard box, an eagle or a sheep herd. A lethal autonomous weapons system ...

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 ...

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 ...

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eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

The term generative AI refers to a relatively new field of AI that can create human-like content, from pictures and videos to poetry and even computer code. To achieve this, several different ...

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 ...

Was that Pope Francis wearing a white puffer jacket inspired by luxury fashion brand Balenciaga? Did former President Donald Trump fall to the street while being arrested by police? The answer is no.