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.