Ciphertext- and Polynomial-Level Optimization for Fully Homomorphic Encryption
Compiler optimisations for RNS-CKKS homomorphic encryption push privacy-preserving computation closer to practical throughput — significant for teams building encrypted-data analytics.
Summary written by editorial AI · Source link below
arXiv:2607.15750v1 Announce Type: new Abstract: Fully homomorphic encryption (FHE) schemes such as RNS-CKKS enable privacy-preserving services by allowing direct computation on encrypted data. While recent FHE compilers optimize FHE programs, they operate at the coarse-grained ciphertext level, where each ciphertext operation comprises a sequence of polynomial operations. At this granularity, the compilers miss optimization opportunities across ciphertext operations. This work presents Recifhe,
External link — opens at arXiv Crypto & Security in a new tab.
More from the Research Desk
- Is That Really My X-Ray? Measuring Internet-Exposed DICOM Services in the Presence of Deception20 Jul
- Characterizing Phishing Pages by JavaScript Capabilities20 Jul
- Intentional Electromagnetic Interference Attacks on Facial Recognition20 Jul
- DoSQ: A Cross-Layer Denial of Service Quality Attack by Exploiting Side Channels in 5G NR20 Jul
- Vogls: a Fast Interactive Full-timing Simulator for Pre-silicon Power Side-Channel Analysis20 Jul