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 ...

Adversarial attacks against the technique that powers game-playing AIs and could control self-driving cars shows it may be less robust than we thought. The soccer bot lines up to take a shot at the ...

Accuracies obtained by the most effective configuration of each of the seven different attacks across the three datasets. The Jacobian-based Saliency Map Attack (JSMA) was the most effective in ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Defenses against adversarial attacks, which in the context of AI refer to ...

The context: One of the greatest unsolved flaws of deep learning is its vulnerability to so-called adversarial attacks. When added to the input of an AI system, these perturbations, seemingly random ...

Artificial intelligence and machine learning (AI/ML) systems trained using real-world data are increasingly being seen as open to certain attacks that fool the systems by using unexpected inputs. At ...

A trio of researchers at Purdue today published pre-print research demonstrating a novel adversarial attack against computer vision systems that can make an AI see – or not see – whatever the attacker ...

As Artificial Intelligence (AI) becomes a bigger part of the IT landscape, cybersecurity is becoming an AI battlefield. The latest and most aggressive attacks in cybersecurity are now leveraging AI to ...