Stealing AI Models Through the API: A Practical Model Extraction Attack
Organizations invest significant resources training proprietary machine learning (ML) models that provide competitive advantages, whether for medical imaging, fraud detection, or recommendation systems. These models represent months of R&D, specialized datasets, and hard-won domain expertise. But what if an attacker could duplicate an expensive machine learning model at a fraction of the cost? Model extraction […]