2 citations · 4 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
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…
AI-Driven Secure Data Sharing: A Trustworthy and Privacy-Preserving Approach
Al Amin, Kamrul Hasan, Sharif Ullah +1
In the era of data-driven decision-making, ensuring the privacy and security of shared data is paramount across various domains. Applying existing deep neural networks (DNNs) to en…
ViT Enhanced Privacy-Preserving Secure Medical Data Sharing and Classification
Al Amin, Kamrul Hasan, Sharif Ullah +1
Privacy-preserving and secure data sharing are critical for medical image analysis while maintaining accuracy and minimizing computational overhead are also crucial. Applying exist…