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 ...

Generative Adversarial Networks Research Report 2026: Market to Expand by $170+ Billion by 2035 - Hyper-Personalized Advertising and Advanced Fraud Detection Drive Enterprise ...

The GANs market is poised for significant growth, driven by AI adoption and advancements in neural networks. Key opportunities include enhancing digital marketing with personalized content, improving ...
ascopubs.org

Using Adversarial Images to Assess the Robustness of Deep Learning Models Trained on Diagnostic Images in Oncology

HealthTree Cure Hub: A Patient-Derived, Patient-Driven Clinical Cancer Information Platform Used to Overcome Hurdles and Accelerate Research in Multiple Myeloma Adversarial images represent a ...
VentureBeat

Defending SOCs Under Siege: Battling Adversarial AI Attacks

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 ...
Dark Reading

Machine Learning Models: A Dangerous New Attack Vector

Threat actors can hijack machine learning (ML) models that power artificial intelligence (AI) to deploy malware and move laterally across enterprise networks, researchers have found. These models, ...
Forbes

AI Ethics Tempted But Hesitant To Use AI Adversarial Attacks Against The Evils Of Machine Learning, Including For Self-Driving Cars

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 ...