Fully Homomorphic Encryption for Private Federated Learning

Privacy-preserving LLM inference with CKKS homomorphic encryption and Private Linear Layer (PLL) protection for LoRA fine-tuned models

A scalable, Fully Homomorphic Encryption (FHE) pipeline that allows for model inference on encrypted data without the need for decryption.

Collaborative Machine Learning approach to train a mode that classifies a person as smoker or non-smoker based on the user data. The distributed approach of training is done with secure model transmissions to central cloud location where Amazon EC2 instance aggregates the new model based on new training received in Homomorphically Encrypted forms

A Two-Party Secure Computation Protocol using Homomorphic Encryption

Privacy-preserving disease risk prediction using the CKKS homomorphic encryption scheme.

This app uses Bluetooth to link a worker’s smartphone with a supervisor’s laptop for live health monitoring. PySyft handles secure biometric authentication, while machine learning detects injuries and visualizes them on a dashboard. Agentic AI responds to critical events by triggering emergency protocols and contacting 911 with location data.

Using fully homomorphic encryption (TenSEAL) for encryption and storage of biometric data.