AI Framework Enhances Secure Data Sharing and Privacy
/ 1 min read
🧩 New AI Framework Enhances Secure Data Sharing While Preserving Privacy. A novel research framework has been developed to improve the security and privacy of shared data, particularly in sensitive domains like healthcare. This approach utilizes a learnable encryption method based on block-pixel operations, integrated with Vision Transformer (ViT) technology, to create unique scrambling patterns for each key. The framework demonstrated a 94% success rate in tests involving sensitive medical datasets, such as MRI scans and histological images, while maintaining computational efficiency and data integrity. It also proved effective against various adversarial attacks, highlighting its robustness as a reliable solution for secure data sharing in critical applications.
