HTseaaat/htadkg

Prototype implementation for the paper Practical Asynchronous High-threshold Distributed Key Generation and Distributed Polynomial Sampling

Running on local machine

Required tools

1. Install Docker. (For Linux, see Manage Docker as a non-root user) to run docker without sudo.)

2. Install docker-compose

Building

1. The image will need to be built (this will likely take a while). Inside the htadkg folder run

$ docker-compose build adkg

Running tests

1. You need to start a shell session in a container. The first run will take longer if the docker image hasn't already been built:

$ docker-compose run --rm adkg bash

2. Then, to test the adkg code locally, i.e., multiple thread in a single docker container, you need to run the following command with parameters:

   • num: Number of nodes,
   • ths: fault-tolerance threshold, and
   • deg: Degree of the ADKG polynomial.

   Note that n>3*t and deg < n-t

$ pytest tests/test_adkg.py -o log_cli=true --num 4 --ths 1 --deg 2 --curve ed25519

Running locally on multiple processes within a docker image

Note: Required tools and build instructions are same as above

Running tests

1. Start a docker image by running $docker-compose run --rm adkg bash

2. Start the ADKG instances $sh scripts/launch-tmuxlocal.sh scripts/adkg-tutorial.py [NUM_NODES]

For this basic test, by default our artifact supports 16, 32, and 64 nodes. To evaluate with arbitrary num,ths and deg, first, generate the corresponding configuration files using gen_config.py. We recommend testing with 16 and 32 nodes for quicker results.

NOTE: Although this process runs NUM_NODES number of ADKG nodes, our artifact only displays the log of the first four nodes. All remaining logs are available at dump.log.

Running in AWS instances

Please refer to aws/README.md for detailed information on how to run the protocol using amazon web services

To cite:

@inproceedings{das2023practical,
   title={Practical Asynchronous High-threshold Distributed Key Generation and Distributed Polynomial Sampling},
   author={Das, Sourav and Xiang, Zhuolun and Kokoris-Kogias, Lefteris and Ren, Ling},
   booktitle={31st USENIX Security Symposium (USENIX Security 23)},
   year={2023}
}