Name | fusion-cryptography JSON |

Version | 0.0.0 JSON |

download | |

home_page | https://github.com/geometry-labs/fusion-cryptography |

Summary | Fusion: highly aggregatable digital signatures using post-quantum lattice cryptography |

upload_time | 2023-06-01 19:51:44 |

maintainer | |

docs_url | None |

author | Geometry Labs |

requires_python | >=3.6 |

license | MIT |

keywords | lattice cryptography fusion signatures |

VCS | |

bugtrack_url | |

requirements | No requirements were recorded. |

Travis-CI | No Travis. |

coveralls test coverage | No coveralls. |

# Fusion cryptography Created by [Geometry Labs](https://www.geometrylabs.io) in partnership with [The QRL Foundation](https://qrl.foundation/) ## Introduction Fusion signatures are based on lattice cryptography for post-quantum security, and are highly aggregatable. They are based on the 2023 whitepaper [Fusion One-Time Non-Interactively-Aggregatable Digital Signatures From Lattices](https://eprint.iacr.org/2023/303). Fusion signatures are elegantly simple in both theory and implementation, reducing the risk of implementation errors. As a one-time signature scheme, Fusion can achieve more narrow tightness gaps in security, smaller signatures, and smaller keys. Our analysis permits parameters to be flexibly tailored to given target security levels and aggregation capacities. Fusion signatures have a number of other generally desirable characteristics: avoiding NTRU assumptions by using only the usual short integer solution assumption, avoiding floating-point arithmetic by using 32-bit signed integers, avoiding trapdoors, and avoiding some issues associated with randomization and statelessness. **Disclaimer**: Fusion algorithms are still undergoing security analysis and this codebase has not been independently audited. ## Installation `pip install fusion-cryptography` ## Usage Here is a little demo showing the full lifecycle of a fusion signature. This includes (1) configuring the cryptographic system, (2) generating multiple keypairs, (3) signing multiple messages, (4) aggregating the signatures, and (5) verifying the result. ```python import random import string from typing import List from fusion.fusion import ( fusion_setup, keygen, sign, aggregate, verify, OneTimeKeyTuple, Params, Signature, OneTimeVerificationKey, ) # >> Set how many N signatures to create and aggregate for the demo num_signatures: int = 2 # 1. Set up the cryptographic system using a security parameter and a seed secpar: int = 256 seed: int = 42 a: Params = fusion_setup(secpar, seed) print(f"Setup completed with security parameter {secpar} and seed {seed}.") # 2. Generate N one-time key pairs keys: List[OneTimeKeyTuple] = [keygen(a, seed) for _ in range(2)] print(f"Generated {len(keys)} key pairs.") # 3. Sign N messages using the key pairs messages: List[str] = [ "".join(random.choices(string.ascii_letters + string.digits, k=20)) for _ in range(num_signatures) ] sigs: List[Signature] = [sign(a, key, message) for key, message in zip(keys, messages)] print(f"Signed {len(messages)} messages.") # 4. Aggregate signatures from the signed messages vks: List[OneTimeVerificationKey] = [key[1] for key in keys] # public keys agg_sig: Signature = aggregate(a, vks, messages, sigs) print("Aggregated the signatures.") # 5. Verify the aggregate signature result_bit, result_message = verify(a, vks, messages, agg_sig) if result_bit: print("Verification successful!") else: print(f"Verification failed! Reason: {result_message}") ``` ## Tests Install packages in `requirements-tests.txt` and run scripts in `tests` folder with `pytest`. ## Contributors Brandon Goodell (lead author), Mitchell P. Krawiec-Thayer

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