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Abstract
The idea of hybrid homomorphic encryption (HHE) is to drastically reduce bandwidth requirements when using homomorphic encryption (HE) at the cost of more expensive computations in the encrypted domain. To this end, various dedicated schemes for symmetric encryption have already been proposed. However, it is still unclear if those ideas are already practically useful, because (1) no cost-benefit analysis was done for use cases and (2) very few implementations are publicly available. We address this situation in several ways. We build an open-source benchmarking framework involving several use cases covering three popular libraries. Using this framework, we explore properties of the respective HHE proposals. It turns out that even medium-sized use cases are infeasible, especially when involving integer arithmetic. Next, we propose Pasta, a cipher thoroughly optimized for integer HHE use cases. Pasta is designed to minimize the multiplicative depth, while also leveraging the structure of two state-of-the-art integer HE schemes (BFV and BGV) to minimize the homomorphic evaluation latency. Using our new benchmarking environment, we extensively evaluate \pasta in SEAL and HElib and compare its properties to 8 existing ciphers in two use cases. Our evaluations show that \pasta outperforms its competitors for HHE both in terms of homomorphic evaluation time and noise consumption, showing its efficiency for applications in real-world HE use cases. Concretely, Pasta outperforms Agrasta by a factor of up to 82, Masta by a factor of up to 6 and Hera up to a factor of 11 when applied to the two use cases.
Original language | English |
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Title of host publication | TCHES 2023 Volume 2023/3 |
Publication status | Published - 2023 |
Event | 25th Conference on Cryptographic Hardware and Embedded Systems: CHES 2023 - Prague, Czech Republic Duration: 10 Sept 2023 → 14 Sept 2023 https://ches.iacr.org/2023/program.php |
Conference
Conference | 25th Conference on Cryptographic Hardware and Embedded Systems |
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Abbreviated title | TCHES |
Country/Territory | Czech Republic |
City | Prague |
Period | 10/09/23 → 14/09/23 |
Internet address |
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- 1 Finished
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DDAI - Explainable, Verifiable and Privacy-Preserving Data-Driven AI
Rechberger, C. (Co-Investigator (CoI)), Lindstaedt, S. (Co-Investigator (CoI)), Trügler, A. (Co-Investigator (CoI)), Pammer-Schindler, V. (Co-Investigator (CoI)), Kern, R. (Co-Investigator (CoI)) & Kowald, D. (Co-Investigator (CoI))
1/01/20 → 31/12/23
Project: Research project