## Abstract

Our main result is a reduction from worst-case lattice problems such as GapSVP 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 GapSVP and SIVP. A main open question is whether this reduction can be made classical (i.e., nonquantum). We also present a (classical) public-key cryptosystem whose security is based on the hardness of the learning problem. By the main result, its security is also based on the worst-case quantum hardness of GapSVP and SIVP. The new cryptosystem is much more efficient than previous lattice-based cryptosystems: the public key is of size (n^{2}) and encrypting a message increases its size by a factor of (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).

Original language | English (US) |
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Article number | 1568324 |

Journal | Journal of the ACM |

Volume | 56 |

Issue number | 6 |

DOIs | |

State | Published - Sep 1 2009 |

## Keywords

- Average-case hardness
- Cryptography
- Lattice
- Public key encryption
- Quantum computation

## ASJC Scopus subject areas

- Software
- Control and Systems Engineering
- Information Systems
- Hardware and Architecture
- Artificial Intelligence