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🎲 A Distributed Randomness Beacon Daemon - Go implementation
https://github.com/drand/drand

cryptography golang hacktoberfest randomness randomness-beacon

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🎲 A Distributed Randomness Beacon Daemon - Go implementation

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# Drand - A Distributed Randomness Beacon Daemon








  

  

  

  

  






Drand (pronounced "dee-rand") is a distributed randomness beacon daemon

written in Golang.






Linked drand nodes collectively produce publicly verifiable,

unbiased and unpredictable random values at

fixed intervals using bilinear pairings and threshold cryptography.






Drand was first developed within the DEDIS

organization, and as of December 2019, is now under the drand organization.




## Table of Contents



- [Goal and Overview](#goal-and-overview)

  - [Public Randomness](#public-randomness)

- [Installation](#installation)

  - [Official release](#official-release)

  - [Manual installation](#manual-installation)

  - [Via Golang](#via-golang)

  - [Via Docker](#via-docker)

- [Usage](#usage)

  - [Run Drand locally](#run-drand-locally)

  - [Create a Drand deployment](#create-a-drand-deployment)

  - [Fetching Public Randomness](#fetching-public-randomness)

  - [Using HTTP endpoints](#using-http-endpoints)

  - [JavaScript client](#javascript-client)

- [Documentation](#documentation)

- [What's Next?](#whats-next)

- [Development](#development)

- [Acknowledgments](#acknowledgments)

- [Coverage](#coverage)

- [Tracing](#tracing)

- [License](#license)



## Goal and Overview



The need for digital randomness is paramount in multiple digital applications

([e]voting, lottery, cryptographic parameters, embedded devices bootstrapping

randomness, blockchain systems etc) as well in non-digital such as statistical

sampling (used for example to check results of an election), assigning court

cases to random judges, random financial audits, etc.  However, constructing a

secure source of randomness is anything but easy: there are countless examples

of attacks where the randomness generation was the culprit (static keys,

non-uniform distribution, biased output, etc).  drand aims to fix that gap by

providing a Randomness-as-a-Service network (similar to NTP servers for time,

or Certificate Authority servers for CAs verification), providing continuous

source of randomness which is:



* Decentralized: drand is a software ran by a diverse set of reputable entities

  on the Internet and a threshold of them is needed to generate randomness,

  there is no central point of failure.

* Publicly verifiable & unbiased: drand periodically delivers publicly

  verifiable and unbiased randomness. Any third party can fetch and verify the

  authenticity of the randomness and by that making sure it hasn't been

  tampered with.



A drand network is operated by a group of organizations around the world that

includes Cloudflare, EPFL, Kudelski Security, Protocol Labs, Celo, UCL, and

UIUC. You can learn more by visiting the

[League of Entropy website](https://leagueofentropy.com), where you can also

see the random values being generated by the network in real time.



### Public Randomness



Generating public randomness is the primary functionality of drand. Public

randomness is generated collectively by drand nodes and publicly available. The

main challenge in generating good randomness is that no party involved in the

randomness generation process should be able to predict or bias the final

output. Additionally, the final result has to be third-party verifiable to make

it actually useful for applications like lotteries, sharding, or parameter

generation in security protocols.



A drand randomness beacon is composed of a distributed set of nodes and has two

phases:



- **Setup:** Each node first generates a *long-term public/private key pair*.

  Then all of the public keys are written to a *group file* together with some

  further metadata required to operate the beacon. After this group file has

  been distributed, the nodes perform a *distributed key generation* (DKG)

  protocol to create the collective public key and one private key share per

  server. The participants NEVER see/use the actual (distributed) private key

  explicitly but instead utilize their respective private key shares for the

  generation of public randomness.

- **Generation:** After the setup, the nodes switch to the randomness

  generation mode. Any of the nodes can initiate a randomness generation round

  by broadcasting a message which all the other participants sign using a

  t-of-n threshold version of the *Boneh-Lynn-Shacham* (BLS) signature scheme

  and their respective private key shares. Once any node (or third-party

  observer) has gathered t partial signatures, it can reconstruct the full BLS

  signature (using Lagrange interpolation). The signature is then hashed using

  SHA-256 to ensure that there is no bias in the byte representation of the

  final output. This hash corresponds to the collective random value and can be

  verified against the collective public key.



## Installation



### Official release



Please go use the latest drand binary in the [release page](https://github.com/drand/drand/releases).



### Manual installation



Drand can be installed via [Golang](https://golang.org/) or

[Docker](https://www.docker.com/). By default, drand saves the configuration

files such as the long-term key pair, the group file, and the collective public

key in the directory `$HOME/.drand/`.



The docker image can also be built manually by running `docker build --build-arg version=$(git describe --tags) --build-arg gitCommit=$(git rev-parse HEAD) -t drandorg/go-drand:latest .` in the project root folder

Additional instructions for running a node or network using docker can be found in the [docker directory](./docker)



### Via Golang



Make sure that you have a working [Golang

installation](https://golang.org/doc/install) and that your

[GOPATH](https://golang.org/doc/code.html#GOPATH) is set.



Then install drand via:

```bash

git clone https://github.com/drand/drand

cd drand

make install

```



### Via Docker



The setup is explained in

[docker/README.md](https://github.com/drand/drand/tree/master/docker/README.md).



## Usage



### Run Drand locally



To run a local demo, you can simply run:

```bash

make demo

```



The script spins up a few drand local processes, performs resharing and other

operations and will continue to print out new randomness every Xs (currently

6s).

For more information, look at the demo [README](https://github.com/drand/drand/tree/master/demo).



A drand beacon provides several public services to clients. A drand node

exposes its public services on a gRPC endpoint as well as a REST JSON endpoint,

on the same port. The latter is especially useful if one wishes to retrieve

randomness from a JavaScript application.  Communication is meant to be protected

through TLS by using a reverse-proxy to perform TLS termination.



### Create a Drand deployment



Consult full instructions at [DEPLOYMENT](https://drand.love/operator/deploy/)



### Fetching Public Randomness



To get the latest public random value, run

```bash

drand get public --round  

```

where `` is the group identity file of a drand node. You can

specify the round number when the public randomness has been generated. If not

specified, this command returns the most recent random beacon.



The JSON-formatted output produced by drand is of the following form:

```json

{

  "round": 367,

  "signature": "b62dd642e939191af1f9e15bef0f0b0e9562a5f570a12a231864afe468377e2a6424a92ccfc34ef1471cbd58c37c6b020cf75ce9446d2aa1252a090250b2b1441f8a2a0d22208dcc09332eaa0143c4a508be13de63978dbed273e3b9813130d5",

  "previous_signature": "afc545efb57f591dbdf833c339b3369f569566a93e49578db46b6586299422483b7a2d595814046e2847494b401650a0050981e716e531b6f4b620909c2bf1476fd82cf788a110becbc77e55746a7cccd47fb171e8ae2eea2a22fcc6a512486d",

  "randomness": "d7aed3686bf2be657e6d38c20999831308ee6244b68c8825676db580e7e3bec6"

}

```



Here `Signature` is the threshold BLS signature on the previous signature value

`Previous` and the current round number. `Randomness` is the hash of

`Signature`, to be used as the random value for this round. The field `Round`

specifies the index of `Randomness` in the sequence of all random values

produced by this drand instance. The **message signed** is therefore the

concatenation of the round number treated as a `uint64` and the previous

signature. At the moment, we are only using BLS signatures on the bls12-381 curves

and the signature is made over G1.



(Note that this command expects access to a drand group member,

this won't work with the current League of Entropy nodes, since they

are not exposing their GRPC endpoints directly.)



### Using HTTP endpoints



This is the recommended way of using drand randomness, but don't forget to validate

the beacons' signatures against the group public key.



One may want to get the distributed key or public randomness by issuing a GET to a

HTTP endpoint instead of using a gRPC client. Here is a basic example on how to

do so with curl.



To get the distributed key, you can use:

```bash

curl 
/group

```



Similarly, to get the latest round of randomness from the drand beacon, you can

use

```bash

curl 
/public/latest

```



### JavaScript client



To facilitate the use of drand's randomness in JavaScript-based applications,

we provide [`drand-client`](https://github.com/drand/drand-client).



For more details on the procedure and instructions on how to use it,

refer to the

[readme](https://github.com/drand/drand-client/blob/master/README.md).



## Documentation



Here is a list of all documentation related to drand:



- To learn more about the protocol, the motivation and its background

  - For a high level presentation of motivations and background, here are some public

  [slides](https://docs.google.com/presentation/d/1t2ysit78w0lsySwVbQOyWcSDnYxdOBPzY7K2P9UE1Ac/edit?usp=sharing)

  about drand or online [video](https://www.youtube.com/watch?v=ydwW2HFFxNI&list=PLhuBigpl7lqu6xWpiXtbEzJQtlMH1tqoG&index=3).

  - [A basic explainer of the cryptography behind drand](https://hackmd.io/@nikkolasg/HyUAgm234),

  - [Protocol Specification](https://drand.love/docs/specification/)

- API documentation

  - [The client-side API documentation of drand](https://hackmd.io/@nikkolasg/HJ9lg5ZTE)

- DevOps/Deployment documentation

  - [Deployment instructions](https://drand.love/operator/deploy/)

  - [Security Model](https://drand.love/docs/security-model/)



As well, here is a list of background readings w.r.t to the cryptography used in

drand:



- [Pairing-based

  cryptography](https://en.wikipedia.org/wiki/Pairing-based_cryptography) and

  [Barreto-Naehrig curves](https://github.com/dfinity/bn).

- [Pedersen's distributed key generation

  protocol](https://link.springer.com/article/10.1007/s00145-006-0347-3) for

  the setup.

- Threshold [BLS

  signatures](https://www.iacr.org/archive/asiacrypt2001/22480516.pdf) for the

  generation of public randomness.

- The resharing scheme used comes from the

  [paper](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.55.2968&rep=rep1&type=pdf)

  from  Y. Desmedt and S. Jajodia.



Note that drand was originally a [DEDIS](https://dedis.epfl.ch/)-owned project that

is now spinning off on its own Github organization. For related previous work

on public randomness, see DEDIS's academic paper [Scalable Bias-Resistant

Distributed Randomness](https://eprint.iacr.org/2016/1067.pdf).



## What's Next?



Although being already functional, drand is still at an early development stage

and there is a lot left to be done. The list of opened

[issues](https://github.com/dedis/drand/issues) is a good place to start. On top

of this, drand would benefit from higher-level enhancements such as the

following:



+ Implement a more [failure-resilient DKG

  protocol](https://eprint.iacr.org/2012/377.pdf) or an approach based on

  verifiable succinct computations (zk-SNARKs, etc).

+ Use / implement a faster pairing based library in JavaScript

+ Add more unit tests

+ Add a systemd unit file



Feel free to submit feature requests or, even better, pull requests ;)



## Development



If you want to contribute to Drand, head over to our [Development documentation](DEVELOPMENT.md).



## Acknowledgments



Thanks to [@herumi](https://github.com/herumi) for providing support on his

optimized pairing-based cryptographic library used in the first version.



Thanks to Apostol Vassilev for its interest in drand and the extensive and

helpful discussions on the drand design.



Thanks to [@Bren2010](https://github.com/Bren2010) and

[@grittygrease](https://github.com/grittygrease) for providing the native

Golang bn256 implementation and for their help in the design of drand and

future ideas.



Finally, a special note for Bryan Ford from the [DEDIS lab](https://dedis.epfl.ch/)

for letting me work on this project and helping me grow it.



## Coverage



- EPFL blog [post](https://actu.epfl.ch/news/epfl-helps-launch-globally-distributed-randomness-/)

- Cloudflare crypto week [introduction

  post](https://new.blog.cloudflare.com/league-of-entropy/) and the more

  [technical post](https://new.blog.cloudflare.com/inside-the-entropy/).

- Kudelski Security blog

  [post](https://research.kudelskisecurity.com/2019/06/17/league-of-entropy/)

- OneZero

  [post](https://onezero.medium.com/the-league-of-entropy-is-making-randomness-truly-random-522f22ce93ce)

  on the league of entropy

- SlashDot

  [post](https://science.slashdot.org/story/19/06/17/1921224/the-league-of-entropy-forms-to-offer-acts-of-public-randomness)

- Duo

  [post](https://duo.com/decipher/the-league-of-entropy-forms-to-offer-acts-of-public-randomness)

- [Liftr](https://liftrinsights.com/liftr-cloud-look-ahead-cloudflare-introduces-the-league-of-entropy-googles-solution-to-keep-data-sets-private-and-more/)

- (French)

  [nextimpact](https://www.nextinpact.com/brief/cloudflare-presente-la-league-of-entropy--pour-obtenir-des-nombres-aleatoires-9074.html)



## Tracing



In the [./docker](./docker) folder, you can use the [docker-compose.tracing.yaml](./docker/docker-compose.tracing.yaml) to spin up the necessary components for monitoring a drand binary in-depth.

To run tracing, you will need to pass the `--traces` command line flag with the endpoint of the tool running in the docker-compose file (or another OpenTelemetry endpoint). You can optionally pass the `--traces-probability` flag to configure how many calls you wish to sample for telemetry.



## License



The drand project is dual-licensed under Apache 2.0 and MIT terms:



- Apache License, Version 2.0, ([LICENSE-APACHE](https://github.com/drand/drand/blob/master/LICENSE-APACHE) or http://www.apache.org/licenses/LICENSE-2.0)

- MIT license ([LICENSE-MIT](https://github.com/drand/drand/blob/master/LICENSE-MIT) or http://opensource.org/licenses/MIT)