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| Content Provider | ACM Digital Library |
|---|---|
| Author | Gentry, Craig Brakerski, Zvika Vaikuntanathan, Vinod |
| Abstract | We present a novel approach to fully homomorphic encryption (FHE) that dramatically improves performance and bases security on weaker assumptions. A central conceptual contribution in our work is a new way of constructing leveled fully homomorphic encryption schemes (capable of evaluating arbitrary polynomial-size circuits), without Gentry's bootstrapping procedure. Specifically, we offer a choice of FHE schemes based on the learning with error (LWE) or ring-LWE (RLWE) problems that have $2^{λ}$ security against known attacks. For RLWE, we have: • A leveled FHE scheme that can evaluate L-level arithmetic circuits with Õ(λ · $L^{3})$ per-gate computation -- i.e., computation quasi-linear in the security parameter. Security is based on RLWE for an approximation factor exponential in L. This construction does not use the bootstrapping procedure. • A leveled FHE scheme that uses bootstrapping as an optimization, where the per-gate computation (which includes the bootstrapping procedure) is $Õ(λ^{2}),$ independent of L. Security is based on the hardness of RLWE for quasi-polynomial factors (as opposed to the sub-exponential factors needed in previous schemes). We obtain similar results to the above for LWE, but with worse performance. Based on the Ring LWE assumption, we introduce a number of further optimizations to our schemes. As an example, for circuits of large width -- e.g., where a constant fraction of levels have width at least λ -- we can reduce the per-gate computation of the bootstrapped version to Õ(λ), independent of L, by batching the bootstrapping operation. Previous FHE schemes all required $Ω(λ^{3.5})$ computation per gate. At the core of our construction is a much more effective approach for managing the noise level of lattice-based ciphertexts as homomorphic operations are performed, using some new techniques recently introduced by Brakerski and Vaikuntanathan (FOCS 2011). |
| Starting Page | 309 |
| Ending Page | 325 |
| Page Count | 17 |
| File Format | |
| ISBN | 9781450311151 |
| DOI | 10.1145/2090236.2090262 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-01-08 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Bootstrapping Modulus reduction Fully homomorphic encryption Learning with errors |
| Content Type | Text |
| Resource Type | Article |
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