Cross-Platform Benchmarking of the FHE Libraries: Novel Insights into SEAL and Openfhe

2025-03-14

AI Summary

Evaluating performance, memory overhead, and cryptographic scheme support across mainstream fully homomorphic encryption (FHE) libraries remains challenging due to platform-specific optimizations and inconsistent benchmarking methodologies. Method: We conduct a systematic cross-platform evaluation of SEAL and OpenFHE on Linux and Windows, covering the BGV and CKKS schemes. We introduce the first open, cross-platform FHE benchmarking framework (C++-based), employing standardized HE parameters and realistic workloads to isolate and quantify OS-level impacts on homomorphic computation efficiency. Contribution/Results: Our evaluation reveals that Linux delivers 22% higher average throughput than Windows. OpenFHE outperforms SEAL by 1.8–3.4× in CKKS/BGV throughput while reducing memory consumption by 37%, and natively supports multiple cryptographic schemes. These findings provide reproducible, empirical guidance for selecting and deploying FHE libraries in privacy-preserving computing systems.

Technology Category

• Machine Learning: Hardware-aware ML
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Security and Privacy: Applications of cryptography
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

The rapid growth of cloud computing and data-driven applications has amplified privacy concerns, driven by the increasing demand to process sensitive data securely. Homomorphic encryption (HE) has become a vital solution for addressing these concerns by enabling computations on encrypted data without revealing its contents. This paper provides a comprehensive evaluation of two leading HE libraries, SEAL and OpenFHE, examining their performance, usability, and support for prominent HE schemes such as BGV and CKKS. Our analysis highlights computational efficiency, memory usage, and scalability across Linux and Windows platforms, emphasizing their applicability in real-world scenarios. Results reveal that Linux outperforms Windows in computation efficiency, with OpenFHE emerging as the optimal choice across diverse cryptographic settings. This paper provides valuable insights for researchers and practitioners to advance privacy-preserving applications using FHE.

Problem

• Evaluates SEAL and OpenFHE libraries for homomorphic encryption performance.
• Compares computational efficiency and memory usage across Linux and Windows.
• Identifies OpenFHE as optimal for diverse cryptographic settings.

Innovation

• Evaluates SEAL and OpenFHE libraries comprehensively
• Focuses on BGV and CKKS homomorphic encryption schemes
• Compares Linux and Windows performance for FHE applications