Sublinear-lookup blockchains and efficient key-value Merkle trees with a flexible storage backend
Sublinear-lookup blockchains and efficient key-value Merkle trees.
Check out the documentation.
This library provides implementations of two cryptographic data structures:
Blockchains with log(n) sublinear traversal, implemented as high-integrity deterministic skip-lists (skipchains). In this kind of blockchain verifying that block b extends block a does not require to download and process all blocks between a and b, but only a logarithmic amount of them.
Verifiable dictionary, implemented as a key-value Merkle tree that guarantees unique resolution. A proof of inclusion of a key-value pair in such a tree also proves that there does not exist another value for a given key somewhere else in the tree.
Both are meant to be used with a content-addressable storage. Each data structure supports logarithmic queries, and logarithmic proofs of inclusion:
Retrievals per lookup
Inclusion proof size
Key-value Merkle tree
with n being the size of the dictionary, or the number of blocks in the case of a chain.
The theoretical details are in the paper.
You can install the library from PyPI:
pip install hippiepug
Then, the easiest way to run the tests is:
python setup.py test
Be sure to check out the usage guide.
The library is a reimplementation of G. Danezis’s hippiehug (hence the name).
This work is funded by the NEXTLEAP project within the European Union’s Horizon 2020 Framework Programme for Research and Innovation (H2020-ICT-2015, ICT-10-2015) under grant agreement 688722.
The hippie pug logo kindly donated by M. Naiem.
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