Sentiment Analysis on Encrypted Data with Homomorphic Encryption

This post details the implementation of sentiment analysis on encrypted data using Fully Homomorphic Encryption (FHE) with Zama's FHE library. It showcases how to encrypt tweet data, perform sentiment analysis on the encrypted data, and decrypt the results. The technical contribution lies in demonstrating the practical application of FHE for privacy-preserving NLP tasks, specifically sentiment analysis, by integrating a transformer model with an FHE-enabled backend.