A General Purpose Transpiler for Fully Homomorphic Encryption (2106.07893v1)

Abstract: Fully homomorphic encryption (FHE) is an encryption scheme which enables computation on encrypted data without revealing the underlying data. While there have been many advances in the field of FHE, developing programs using FHE still requires expertise in cryptography. In this white paper, we present a fully homomorphic encryption transpiler that allows developers to convert high-level code (e.g., C++) that works on unencrypted data into high-level code that operates on encrypted data. Thus, our transpiler makes transformations possible on encrypted data. Our transpiler builds on Google's open-source XLS SDK (https://github.com/google/xls) and uses an off-the-shelf FHE library, TFHE (https://tfhe.github.io/tfhe/), to perform low-level FHE operations. The transpiler design is modular, which means the underlying FHE library as well as the high-level input and output languages can vary. This modularity will help accelerate FHE research by providing an easy way to compare arbitrary programs in different FHE schemes side-by-side. We hope this lays the groundwork for eventual easy adoption of FHE by software developers. As a proof-of-concept, we are releasing an experimental transpiler (https://github.com/google/fully-homomorphic-encryption/tree/main/transpiler) as open-source software.

• The paper presents a modular transpiler that transforms high-level C++ code into TFHE-based Boolean operations for encrypted computations.
• The paper leverages Google's XLS SDK and TFHE library to convert C++ into an intermediate representation, optimize it, and perform Booleanification for secure processing.
• The paper paves the way for non-expert developers by reducing cryptographic barriers and accelerating FHE research through a flexible, modular design.

A General Purpose Transpiler for Fully Homomorphic Encryption

The paper "A General Purpose Transpiler for Fully Homomorphic Encryption" addresses a significant challenge in the field of cryptographic computing: enabling software developers, who are not cryptography experts, to leverage fully homomorphic encryption (FHE). The transpiler introduced in this work transforms high-level code, such as C++, that functions on plaintext into code that can operate on encrypted data. This makes it possible to perform computations on encrypted inputs without revealing the underlying data.

Technical Approach

The authors build upon Google's open-source XLS SDK and utilize the TFHE library for low-level FHE operations. The transpiler is designed to be modular, supporting flexibility in the choice of FHE libraries as well as the input and output programming languages. This modularity is intended to accelerate FHE research by allowing comparative analysis of different schemes.

Underlying Technologies

The transpiler relies heavily on two external components:

1. XLS: This SDK is crucial for translating high-level language operations into an intermediate representation (XLS IR), which is optimized before being translated into Boolean operations for TFHE.
2. TFHE: Serving as the underlying FHE library, TFHE enables the rapid execution of gate operations via an efficient bootstrapping process, crucial for maintaining noise within tolerable limits during computations.

Transpiler Design and Execution Process

The transpiler's process is composed of several steps:

• C++ Frontend: Convert C++ code into XLS IR.
• Optimizer: Perform optimizations on the IR to reduce complexity.
• Booleanifier: Transform the optimized IR into Boolean operations.
• FHE IR Translator: Convert Boolean IR to TFHE-based C++ code.

Features and Utilities

The transpiler includes several notable features:

• Modular Design: Allows for swapping input languages and FHE libraries, accommodating multiple research and application contexts.
• TFHE Interface Utilities: Simplifies interactions with FHE-processed data via a user-friendly API.
• Debugging Tools: Offers a Boolean backend for debugging without FHE, addressing a common obstacle in real-world FHE application.

Practical Implications and Future Directions

Practically, the transpiler serves as a prototype, highlighting the feasibility of implementing fully homomorphic encryption in standard programming environments. While still experimental, the transpiler showcases a path toward broader adoption of FHE, reducing the entry barrier for non-expert developers.

Looking forward, there are several potential areas for improvement and extension:

• Performance Enhancements: Further optimization is essential to reduce execution times for complex FHE operations.
• Support for Arithmetic Operations: Introducing native arithmetic operations via techniques like SIMD-style packing could significantly enhance performance for arithmetic-heavy tasks.
• Parameter Selection: Automating parameter tuning specific to given computations could streamline deployment.

The authors also suggest leveraging programmable bootstrapping for optimizations, which could enable high-performance computation of arbitrary functions. Moreover, exploration into mixed compute environments could unlock additional performance gains.

Conclusion

The work presented in this paper contributes meaningfully to the field of FHE by addressing the practical challenges faced by non-expert developers. It lays a foundation for future research and development in FHE applications, providing insights into modular and flexible approaches for cryptographic processing. As FHE schemes and their implementations mature, solutions like this transpiler may accelerate the transition from theoretical exploration to widespread application in secure data processing.