The Weizmann Institute of Science
Faculty of Mathematics and Computer Science
Walmart Lecture Series in Cryptography and Complexity
Lecture Hall, Room 1, Ziskind Building
on Wednesday, June 15, 2011
14:00 - 16:00
Zvika Brakerski
will speak on
Efficient Fully Homomorphic Encryption
from (Standard) LWE
Abstract:
In fully homomorphic encryption, it is possible to transform an encryption of a
message, $m$, into an encryption of any (efficient) function of that message,
$f(m)$, without knowing the secret key. This property makes it into a very
useful cryptographic building block.
We present a fully homomorphic encryption scheme that is based solely on the
(standard) learning with errors (LWE) assumption. Applying known results on
LWE, the security of our scheme is based on the worst-case hardness of short
vector problems on arbitrary lattices. As icing on the cake, our scheme is
quite efficient, and has very short ciphertexts.
Our construction improves upon previous works in two aspects:
1. We show that ``somewhat homomorphic'' encryption can be based on LWE,
using a new {\it re-linearization} technique. In contrast, all previous
schemes relied on complexity assumptions related to ideals in various
rings.
2. We deviate from the ``squashing paradigm'' used
in all previous works. We introduce a new {\it dimension reduction}
technique, which shortens the ciphertexts and reduces the decryption
complexity of our scheme, without introducing additional assumptions.
In contrast, all previous works required an additional, very strong
assumption (namely, the sparse subset sum assumption).
Since our scheme has very short ciphertexts, we use it to construct an
asymptotically-efficient LWE-based single-server private information retrieval
(PIR) protocol. The communication complexity of our protocol (in the public-key
model) is $k \cdot {\rm polylog}\,k+\log |DB|$ bits per single-bit query, which
is better than any known scheme. Previously, it was not known how to achieve a
communication complexity of even ${\rm poly}(k, \log|DB|)$ based on LWE.
Joint work with Vinod Vaikuntanathan.