Abstract
This research proposes approximate computing techniques to accelerate homomorphic encryption (HE). In
particular, the CKKS encryption scheme for approximate numbers is targeted. There is a requirement for HE in
services dealing with confidential data, however current constructions are not efficient enough for real-time
applications. A homomorphic encryption scheme which uses approximate arithmetic (showing faster results
than previous HE schemes) already exists, the CKKS scheme, and this research applies a variation of the
approximate computing techniques of task skipping and depth reduction (derived from loop perforation) to
determine whether further approximating the functions evaluated using CKKS scheme can have a positive
impact on performance of homomorphic evaluation. This is demonstrated via the evaluation of the logistic
and exponential functions that this is possible, showing positive results. The speed up in running time for
HE with task skipping is between 12.1% and 45.5%, depth reduction gives 35-45.5% speed-up with a small
error difference than task skipping alone. The combination of both techniques corresponds to a halving of
the running time, at the cost of increased error. This novel approach to further approximate homomorphic
encryption shows that it is possible for certain functions, where running time is of paramount importance, that
further approximations can be made with a lower-impacting greater error.
particular, the CKKS encryption scheme for approximate numbers is targeted. There is a requirement for HE in
services dealing with confidential data, however current constructions are not efficient enough for real-time
applications. A homomorphic encryption scheme which uses approximate arithmetic (showing faster results
than previous HE schemes) already exists, the CKKS scheme, and this research applies a variation of the
approximate computing techniques of task skipping and depth reduction (derived from loop perforation) to
determine whether further approximating the functions evaluated using CKKS scheme can have a positive
impact on performance of homomorphic evaluation. This is demonstrated via the evaluation of the logistic
and exponential functions that this is possible, showing positive results. The speed up in running time for
HE with task skipping is between 12.1% and 45.5%, depth reduction gives 35-45.5% speed-up with a small
error difference than task skipping alone. The combination of both techniques corresponds to a halving of
the running time, at the cost of increased error. This novel approach to further approximate homomorphic
encryption shows that it is possible for certain functions, where running time is of paramount importance, that
further approximations can be made with a lower-impacting greater error.
| Original language | English |
|---|---|
| Title of host publication | The 17th International Conference on Security and Cryptography - SECRYPT 2020 |
| Publisher | Springer |
| Publication status | Accepted - 15 Apr 2020 |
| Event | The 17th International Conference on Security and Cryptography - SECRYPT 2020 - Lieusant, Paris, Italy Duration: 08 Jul 2020 → 10 Jul 2020 http://www.secrypt.icete.org/Home.aspx |
Conference
| Conference | The 17th International Conference on Security and Cryptography - SECRYPT 2020 |
|---|---|
| Abbreviated title | SECRYPT 2020 |
| Country | Italy |
| City | Paris |
| Period | 08/07/2020 → 10/07/2020 |
| Internet address |
Keywords
- Homomorphic Encryption
- Approximate Computing
- Task skipping
- depth reduction
- loop perforation
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Cite this
Khanna, S., & Rafferty, C. (Accepted/In press). Accelerating Homomorphic Encryption using Approximate Computing Techniques. In The 17th International Conference on Security and Cryptography - SECRYPT 2020 Springer.