Paper 2024/1561

FLUENT: A Tool for Efficient Mixed-Protocol Semi-Private Function Evaluation

Abstract

In modern business to customer interactions, handling private or confidential data is essential. Private Function Evaluation (PFE) protocols ensure the privacy of both the customers' input data and the business' function evaluated on it which is often sensitive intellectual property (IP). However, fully hiding the function in PFE results in high performance overhead. Semi-Private Function Evaluation (SPFE) is a generalization of PFE to only partially hide the function, whereas specific non-critical components remain public. Our paper introduces a novel framework designed to make SPFE accessible to non-experts and practical for real-world deployments. To achieve this, we improve on previous SPFE solutions in two aspects. First, we enhance the developer experience by leveraging High-Level Synthesis (HLS), making our tool more user-friendly than previous SPFE frameworks. Second, we achieve a $$ speedup compared to the previous state-of-the-art through more efficient underlying constructions and the usage of Lookup Tables (LUTs). We evaluate the performance of our framework in terms of communication and runtime efficiency. Our final implementation is available as an open-source project, aiming to bridge the gap between advanced cryptographic protocols and their practical application in industry scenarios.