2 papers
cs.CR2026
AutoPoly-HE: Autonomous Design of Polynomial Activations for Privacy-Preserving Encrypted Inference
Zeinab Elkhatib, Kamrul Hasan, Ali Sekmen +2
Privacy-preserving machine learning has become critical for deploying artificial intelligence in sensitive domains such as healthcare, finance, and infrastructure monitoring. Homom…
cs.CR2025
PRISM: Privacy-preserving Inference System with Homomorphic Encryption and Modular Activation
Zeinab Elkhatib, Ali Sekmen, Kamrul Hasan
With the rapid advancements in machine learning, models have become increasingly capable of learning and making predictions in various industries. However, deploying these models i…