VentureBeat

Adversarial attacks in machine learning: What they are and how to stop them

Adversarial machine learning, a technique that attempts to fool models with deceptive data, is a growing threat in the AI and machine learning research community. The most common reason is to cause a ...
Nature

Adversarial Machine Learning

Adversarial machine learning studies the creation and defence against inputs—known as adversarial examples—that are intentionally perturbed to mislead trained models. Deep networks and other ...
techtarget

Adversarial machine learning: Threats and countermeasures

Machine learning offers numerous benefits for organizations and individuals, such as automating routine tasks or discovering trends and patterns in vast data sets. However, all these benefits come ...
Infosecurity-magazine.com

#InfosecurityEurope: Preparing for Adversarial Machine Learning Attacks

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 ...
Forbes

Adversarial Attacks On AI Systems

We are witnessing a rapid advancement of AI and its impact across various industries. However, with great power comes great responsibility, and one of the emerging challenges in the AI landscape is ...
AFCEA

Adversarial Machine Learning Poses a New Threat to National Security

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 ...
Cisco

Cisco Co-Authors Update to the NIST Adversarial Machine Learning Taxonomy

The rapid evolution and enterprise adoption of AI has motivated bad actors to target these systems with greater frequency and sophistication. Many security leaders recognize the importance and urgency ...