To kick-off Crypto Week 2019, we are really excited to announce a new solution to a long-standing problem in cryptography. To get a better understanding of the technical side behind this problem, please refer to the next post for a deeper dive.

Everything from cryptography to big money lottery to quantum mechanics requires some form of randomness. But what exactly does it mean for a number to be randomly generated and where does the randomness come from?

Generating randomness dates back three thousand years, when the ancients rolled “the bones” to determine their fate. Think of lotteries-- seems simple, right? Everyone buys their tickets, chooses six numbers, and waits for an official to draw them randomly from a basket. Sounds like a foolproof solution. And then in 1980, the host of the Pennsylvania lottery drawing was busted for using weighted balls to choose the winning number. This lesson, along with the need of other complex systems for generating random numbers spurred the creation of random number generators.

Just like a lottery game selects random numbers unpredictably, a random number generator is a device or software responsible for generating sequences of numbers in an unpredictable manner. As the need for randomness has increased, so has the need for constant generation of substantially large, unpredictable numbers. This is why organizations developed publicly available randomness beacons -- servers generating completely unpredictable 512-bit strings (about 155-digit numbers) at regular intervals.

Now, you might think using a randomness beacon for random generation processes, such as those needed for lottery selection, would make the process resilient against adversarial manipulation, but that’s not the case. Single-source randomness has been exploited to generate biased results.

Today, randomness beacons generate numbers for lotteries and election audits -- both affect the lives and fortunes of millions of people. Unfortunately, exploitation of the single point of origin of these beacons have created dishonest results that benefited one corrupt insider. To thwart exploitation efforts, Cloudflare and other randomness-beacon providers have joined forces to bring users a quorum of decentralized randomness beacons. After all, eight independent globally distributed beacons can be much more trustworthy than one!

We’re happy to introduce you to ....

THE LEAGUE …. OF …. ENTROPY !!!!!!

What is a randomness beacon?

A randomness beacon is a public service that provides unpredictable random numbers at regular intervals.

drand (pronounced dee-rand) is a distributed randomness beacon developed by Nicolas Gailly; with the help of Philipp Jovanovic, and Mathilde Raynal. The drand project originated from the research paper Scalable Bias-Resistant Distributed Randomness published at the 2017 IEEE Symposium on Security and Privacy by Ewa Syta, Philipp Jovanovic, Eleftherios Kokoris Kogias, Nicolas Gailly, Linus Gasser, Ismail Khoffi, Michael J. Fischer, Bryan Ford, from the Decentralized/Distributed Systems (DEDIS) lab at EPFL, Yale University, and Trinity College Hartford, with support from Research Institute.

For every randomness generation round, drand provides the following properties, as specified in the research paper:

Availability - The distributed randomness generation completes successfully with high probability.

- The distributed randomness generation completes successfully with high probability. Unpredictability - No party learns anything about the random output of the current round, except with negligible probability, until a sufficient number of drand nodes reveals their contributions in the randomness generation protocol.

- No party learns anything about the random output of the current round, except with negligible probability, until a sufficient number of drand nodes reveals their contributions in the randomness generation protocol. Unbiasability - The random output represents an unbiased, uniformly random value, except with negligible probability.

- The random output represents an unbiased, uniformly random value, except with negligible probability. Verifiability - The random output is third-party verifiable against the collective public key computed during drand's setup. This serves as the unforgettable attestation that the documented set of drand nodes ran the protocol to produce the one-and-only random output, except with negligible probability.

Entropy measures the unpredictable nature of a number. For randomness, the more entropy the better, so naturally it’s where we got our name, the League of Entropy.

Our founding members are contributing their individual high-entropy sources to provide a more random and unpredictable beacon to generate publicly verifiable random values every sixty seconds. The fact that the drand beacon is decentralized and built using appropriate, provably-secure cryptographic primitives, increases our confidence that it possesses all the aforementioned properties.

This global network of servers generating randomness ensures that even if a few servers are offline, the beacon continues to produce new numbers by using the remaining online servers. Even if one or two of the servers or their entropy sources were to be compromised, the rest will still ensure that the jointly-produced entropy is fully unpredictable and unbiasable.

Who exactly is running this beacon? Currently, The League of Entropy is a consortium of global organizations and individual contributors, including: Cloudflare, Protocol Labs researcher Nicolas Gailly, University of Chile, École polytechnique fédérale de Lausanne (EPFL), Kudelski Security, and EPFL researchers, Philipp Jovanovic and Ludovic Barman.

Meet the League of Entropy

Cloudflare’s LavaRand: LavaRand sources her high entropy from Cloudflare’s wall of lava lamps at our San Francisco Headquarters. The unpredictable flow of “lava” inside the lamps is used as an input to a camera feed into a CSPRNG (Cryptographically Secure PseudoRandom Number Generator) that generates the random value.

EPFL’s URand: URand’s power comes from the local randomness generator present on every computer at /dev/urandom. The randomness input is collected from inputs such as keyboard presses, mouse clicks, network traffic, etc. URand bundles these random inputs to produce a continuous stream of randomness.

UChile’s Seismic Girl: Seismic Girl extracts super verifiable randomness from five sources queried every minute. These sources include: seismic measurements of shakes and earthquakes in Chile; a stream from a local radio station; a selection of Twitter posts; data from the Ethereum blockchain; and their own off-the-shelf RNG card.

Kudelski Security’s ChaChaRand: ChaChaRand uses a CRNG (Cryptographic Random Number Generator) based on the ChaCha20 stream cipher.

Protocol Labs’ InterplanetaryRand: InterplanetaryRand uses the power of entropy to ensure protocol safety across space and time by using environmental noise and the Linux PRNG, supplemented by CPU-sourced randomness (RdRand).

Together, our heroes are committed to #savetheinternet by combining their randomness to form a globally distributed and cryptographically verifiable randomness beacon.

Public versus Private Randomness

Different types of randomness are needed for different types of applications.

The trick to generating secure cryptographic keys is to use large, privately-generated random numbers that no one else can predict. With randomness beacons publicly generating and announcing random numbers, users should NOT be using the output of a randomness beacon for their secret keys, as these numbers are accessible by anyone. If an attacker can guess the random number that a user’s private cryptographic key was derived from, they can crack their system and decrypt confidential information. This simply means that random numbers generated by a public beacon are not safe to use for encryption keys: not because there’s anything wrong with the randomness, but simply because the randomness is public.

Clients using the drand beacon can request private randomness from some or all of the drand nodes if they would like to generate a random value that will not be publicly announced. For more information on how to do this, check the developer docs .

On the other hand, public randomness is often employed by users requiring a randomness value that is not supposed to be secret but whose generation must be transparent, fair, and unbiased. This is perfect for many purposes such as games, lotteries, and election auditing, where the auditor and the public require transparency into when and how and how fairly the random value was generated.

The League of Entropy provides public randomness that any user can retrieve from leagueofentropy.com. Users will be able to view the 512-bit string value that is generated every 60 seconds. Why 60 seconds? No particular reason. Theoretically, the randomness generation can go as fast as the hardware allows, but it’s not necessary for most use cases. Values generated every 60 seconds give users 1440 random values in one 24-hour period.

*FRIENDLY REMINDER: THIS RANDOMNESS IS PUBLIC. DO NOT USE IT FOR PRIVATE CRYPTOGRAPHIC KEYS*

Why does public randomness matter?

Election auditing

In the US, most elections are followed by an audit to verify they were unbiased and conducted fairly. Robust auditing systems increase voter confidence by improving election officials’ ability to respond effectively to allegations of fraud, and to detect bugs in the system.

Currently, most election ballots and precincts are randomly chosen by election officials. This approach is potentially vulnerable to bias by a corrupt insider who might select certain precincts to present a preferred outcome. Even in a situation where every voter district was tampered with, by using a robust, distributed, and most importantly, unpredictable and unbiasable beacon, election auditors can trust that a small sample of districts are enough to audit, as long as an attacker cannot predict district selection.

In Chile, election poll workers are randomly selected from a pool of eligible voters. The University of Chile’s Random UChile project has been working on a prototype that uses their randomness beacon for this process. Alejandro Hevia, leader of Random UChile, believes that for election auditing, public randomness is important for transparency and distributed randomness gives people the ability to trust the unlikeliness that multiple contributors to the beacon colluded, as opposed to trusting a single entity.

Lotteries

From 2005 to 2014, the information security director for the Multi-State Lottery Association, Eddie Tipton, rigged a random number generator and won the lottery six times!

Tipton could predict the winning numbers by skipping the standard random seeding process. He was able to insert into the function of the random number generator code that checked the date, day of the week, and time. If these three variables did not align, the random number generator used radioactive material and a Geiger counter to generate a random seed. If the variables aligned as surreptitiously programmed, which usually only happened once a year, then it would generate the seed using a 7-variable formula fed into a Mersenne Twister, a pseudo random-number generator.

Tipton knew these 7 variables. He knew the small pool of numbers that might be the seed. This knowledge allowed him to predict the results of the Mersenne Twister. This is a scam which a distributed randomness beacon can make substantially more difficult, if not impossible.

Rob Sand, the former Iowa Assistant Attorney General and current Iowa State Auditor who prosecuted the Tipton cases, is also an advocate for improved controls. He said:

*“There is no excuse for an industry that rakes in $80 billion in annual revenue not to use the most sophisticated, truly random means available to ensure integrity.” *

Distributed ledger platforms

In many cryptocurrencies and blockchain-based distributed computing platforms, such as Ethereum, there is often a need for random selection at the application layer. One solution to prevent bias for such a random selection is to use a distributed randomness beacon like drand to generate the random value. Justin Drake, researcher at the Ethereum Foundation, believes "randomness from a drand-type federation could be a particularly good match for real-time decentralized applications on Ethereum such as live gaming and gambling". This is due to the possibility to deliver ultra-low latency randomness applicable for a broad range of application where public randomness is required.

Let’s get you on drand!

To learn more about the League of Entropy and how to use the distributed randomness beacon, visit https://leagueofentropy.com. The website periodically displays the randomness generated by the network, and you can even see previously generated values. Go ahead, try it out!

How to join the league:

Want to join the league?? We’re not exclusive!

If you are an organization or an individual who is interested in contributing to the drand beacon, check out the developer docs for more information regarding the requirements for setting up a server and joining the existing group. drand is currently in its beta release phase and an approval request must be sent to [email protected] in order to be approved as a contributing server.

Looking into the future

It only makes sense that the Internet of the future will demand unpredictable randomness beacons. The League of Entropy is out there now, creating the basis for future systems to leverage trustworthy public randomness. Our goal is to increase user trust and provide a one-stop shop for all your public entropy needs. Come, join us!



