Accelerating Homomorphic Encryption using Approximate Computing Techniques

Shabnam Khanna*, Ciara Rafferty*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Downloads (Pure)

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%
Original languageEnglish
Title of host publicationThe 17th International Conference on Security and Cryptography - SECRYPT 2020: Proceedings
Pages380-387
Number of pages8
DOIs
Publication statusEarly online date - 29 Apr 2020
EventThe 17th International Conference on Security and Cryptography - SECRYPT 2020 - Lieusant, Paris, Italy
Duration: 08 Jul 202010 Jul 2020
http://www.secrypt.icete.org/Home.aspx

Conference

ConferenceThe 17th International Conference on Security and Cryptography - SECRYPT 2020
Abbreviated titleSECRYPT 2020
CountryItaly
CityParis
Period08/07/202010/07/2020
Internet address

Keywords

  • Homomorphic Encryption
  • Approximate Computing
  • Task skipping
  • depth reduction
  • loop perforation

Fingerprint Dive into the research topics of 'Accelerating Homomorphic Encryption using Approximate Computing Techniques'. Together they form a unique fingerprint.

Cite this