HEProfiler: an in-depth profiler of approximate homomorphic encryption libraries

Abstract Fully Homomorphic Encryption (FHE) allows computation on encrypted data. Various software libraries have implemented the approximate-arithmetic FHE scheme CKKS [1], which is highly useful for applications in machine learning and data analytics; each of these libraries have differing performance and features. It is useful for developers and researchers to learn details about these libraries’ performance and their differences. Some previous work has profiled FHE and CKKS implementations for this purpose, but these comparisons are limited in their fairness and completeness. In this article, we compare four major libraries supporting the CKKS scheme. Working with the maintainers of each of the PALISADE, Microsoft SEAL, HElib, and HEAAN libraries, we devise methods for fair comparisons of these libraries, even with their widely varied development strategies and library architectures. To show the practical performance of these libraries, we present HEProfiler, a simple and extensible framework for profiling C++ FHE libraries. Our experimental evaluation is complete in both the scope of tasks tested and metrics evaluated, allowing us to draw conclusions about the behaviors of different libraries under a wide range of real-world workloads. This is the first work giving experimental comparisons of different bootstrapping-capable CKKS libraries.

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Institutions

Publication Details

Journal
Journal of Cryptographic Engineering
Published
2025-05-27
DOI
https://doi.org/10.1007/s13389-025-00377-5
Citations
3
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
7.44
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article

HEProfiler: an in-depth profiler of approximate homomorphic encryption libraries

Taeho Jung, Colin McKechney, Nirajan Koirala, Jonathan Takeshita
3 citations
Journal of Cryptographic Engineering
Cryptography and Data Security
7.44
article

HEProfiler: an in-depth profiler of approximate homomorphic encryption libraries

Taeho Jung, Colin McKechney, Nirajan Koirala, Jonathan Takeshita
article en
3 citations

Abstract

Abstract Fully Homomorphic Encryption (FHE) allows computation on encrypted data. Various software libraries have implemented the approximate-arithmetic FHE scheme CKKS [1], which is highly useful for applications in machine learning and data analytics; each of these libraries have differing performance and features. It is useful for developers and researchers to learn details about these libraries’ performance and their differences. Some previous work has profiled FHE and CKKS implementations for this purpose, but these comparisons are limited in their fairness and completeness. In this article, we compare four major libraries supporting the CKKS scheme. Working with the maintainers of each of the PALISADE, Microsoft SEAL, HElib, and HEAAN libraries, we devise methods for fair comparisons of these libraries, even with their widely varied development strategies and library architectures. To show the practical performance of these libraries, we present HEProfiler, a simple and extensible framework for profiling C++ FHE libraries. Our experimental evaluation is complete in both the scope of tasks tested and metrics evaluated, allowing us to draw conclusions about the behaviors of different libraries under a wide range of real-world workloads. This is the first work giving experimental comparisons of different bootstrapping-capable CKKS libraries.

Journal of Cryptographic EngineeringVol. 15(2)
University of Notre Dame (US), Tokyo Institute of Technology (JP)
Openalex Percentile: Top 3%
Cryptography and Data Security
7.44
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