on lattices, learning with errors, random linear codes, and cryptography
Our main result is a reduction from worst-case lattice problems such as SVP and SIVP to a certain learning problem. This learning problem is a natural extension of the 'learning from parity with error' problem to higher moduli. It can also be viewed as the problem of decoding from a random linear code. This, we believe, gives a strong indication that these problems are hard. Our reduction, however, is quantum. Hence, an efficient solution to the learning problem implies a quantum algorithm for SVP and SIVP. A main open question is whether this reduction can be made classical.Using the main result, we obtain a public-key cryptosystem whose hardness is based on the worst-case quantum hardness of SVP and SIVP. Previous lattice-based public-key cryptosystems such as the one by Ajtai and Dwork were only based on unique-SVP, a special case of SVP. The new cryptosystem is much more efficient than previous cryptosystems: the public key is of size  ( n 2 ) and encrypting a message increases its size by  ( n )(in previous cryptosystems these values are  ( n 4 ) and  ( n 2 ), respectively). In fact, under the assumption that all parties share a random bit string of length  ( n 2 ), the size of the public key can be reduced to  ( n ).
lattice cryptography quantum computation average-case hardness public key encryption