FPT: A Fixed-Point Accelerator for Torus Fully Homomorphic Encryption
Open accessAbstract
Fully Homomorphic Encryption (FHE) is a technique that allows computation on encrypted data. It has the potential to drastically change privacy considerations in the cloud, but high computational and memory overheads are preventing its broad adoption. TFHE is a promising Torus-based FHE scheme that heavily relies on bootstrapping, the noise-removal tool invoked after each encrypted logical/arithmetical operation.
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The ARMv8-A architecture exhibits comparable timing jitter profiles to x86 and Apple Silicon, ensuring consistent entropy yields across platforms.
“Recent benchmarks confirm that the ARMv8-A architecture exhibit comparable timing jitter profiles to x86 and Apple Silicon24, ensuring consistent entropy yields across platforms.”
From Raw QPP-RNG randomness via system jitter across platforms: a NIST SP 800-90B evaluation (2025) · cites this paper as [24]
The Evaluation and Comparison section benchmarks an FPGA accelerator, and Table 4 compares homomorphic-encryption bootstrapping performance across platforms; neither addresses timing jitter or entropy yields. Searches for ARMv8-A, x86, Apple Silicon, timing jitter, and cross-platform entropy found no relevant passage in our copy. Page numbers were not available. (LLM, conf=0.77)
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Cited by
Sorted by citations
Raw QPP-RNG randomness via system jitter across platforms: a NIST SP 800-90B evaluation
Vrana, G., Lou, D., & Kuang, R. (2025) · Scientific Reports · doi:10.1038/s41598-025-13135-8 · Cited by 5 · see citing works
- Authors
- Van Beirendonck, M., D'Anvers, J.-P., Turan, F., & Verbauwhede, I.
- Affiliations
- COSIC, KU Leuven, Leuven, Belgium
- KU Leuven (BE)
- Venue
- Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security
- Publisher
- ACM
- Published
- 2023-11-15
- Pages
- 741-755
- ISSN
- 1543-7221 (ISSN-L)
- OpenAlex
- W4388857848
- Cited by
- 38
- References
- 54
- Citations by year
- 2026: 13 · 2025: 11 · 2024: 11 · 2023: 3
- FWCI
- 6.75
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM SIGSAC Conference on Computer and Communications Security (CCS) (publishedVersion)
- Lirias (acceptedVersion, other-oa)
- arXiv (Cornell University) (submittedVersion, cc-by)
- Lirias (KU Leuven) (submittedVersion, other-oa)
- arXiv (Cornell University) (cc-by)
- Funders
- FWO PhD Fellow (1SD5621N)
- Research Council KU Leuven (C16/15/058)
- Horizon 2020 ERC Advanced Grant (10102000)
- FWO Post-Doctoral Fellow (133185)
- CyberSecurity Research Flanders (VR20192203)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptographic Implementations and Security
- Physical Sciences › Computer Science › Information Systems › Cryptography and Residue Arithmetic
- Keywords
- fully homomorphic encryption, TFHE, bootstrapping, noise reduction, fixed-point arithmetic, hardware accelerators, cloud privacy, encrypted data processing
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