In September 2013, the denunciator Edward Snowden revealed that the American and British intelligence agencies had managed a large part of the Internet users of the online encryption used to keep their private personal data. The snowen solution has appeared ironic to many: adopting an end -to -end encryption massmaking mass monitoring prohibitive and heavy.
In end -to -end encryption, an algorithm converts the readable data (text in clear) into an illegible form (ciphertext) using a chain of numbers and letters called a key. A user with the key can transform it into a decryption algorithm, which will use it to transform the encrypted text into a clear text. The success of any encryption method thus depends on the secret of the key.
To prevent an unauthorized person from guessing the key, they must be random enough, that is to say lacking predictable models.
How can you get a sufficiently random key? For the Cybersecurity Company Cloudflare, the response lies in a funky invention of 1963: the lava lamp.
A lava lamp includes a glass container with waxing stains suspended in water and placed on an incandescent bulb. The heat of the bulb melts the wax and raises the droplets. When the droplets reach the top of the container, they cool and fall down, start the cycle again. The rising droplets in a lava lamp do not take the same shape twice. In other words, the forms are “always random”.
At the headquarters of Cloudflare in San Francisco in the United States, the company organized a hundred lava lamps on one of its walls. A camera periodically takes photos of the wall and computers convert each pixel of the image into numerical value. Thus, each image generates a chain of numbers (called seed) which then entered an algorithm to generate a encryption key.
A lava lamp shelf. | Photo credit: Dean Hochman (CC by)
However, there are two problems. One, even the “random coherent” movements of the lava lamp, are determined in theory by the laws of thermodynamics, the branch of physics which deals with the way in which heat moves in a system (for example the glass container with water and wax) and how it affects the properties of the material it contains. At least on paper, it makes the seeds foreseeable.
Second, even if the seed is practically random, the algorithm used to generate the key is deterministic, that is to say, non-random. In other words, if a person takes the hand on the seed, they can generate exactly the same key using the algorithm. This is why such algorithms, which are commonplace in most encryption systems today, are called generators of pseudorandoms.
The real random has been elusive – but scientists have known for some time when they could best hope to find it: quantum mechanics, where randomness abounds.
Quantum random
Quantum mechanics is the study of how matter and light behave in atomic and subatomic fields. To these scales, theories of physics are no longer able to make predictions with certainty. Like Gautam A. Kavuri, a quantum communication researcher at the University of Colorado, Boulder (CUB) in the United States, said it, the “result of a measure (in the quantum field) cannot be known before a measure is carried out”.
Consider the case of a photon, the particle of light. Each photon has an oscillating electromagnetic field. The direction in which the oscillate field is called the photon polarization. Depending on the laws of quantum mechanics, the polarization of a photon can be both horizontal and vertical (or left and right) until it is measured – just like a piece thrown into the air is both “heads” and “tails” until it landed. It is only at the time of the measure that polarization becomes one of the two, and this choice is random.
In an article published in Nature In June, Kavuri as well as a team of researchers from the CUB and the National Institute of Standards and Technologies (NIST) in the same city reported this as a source to generate really random numbers.
Once generated, the team broadcasts the figures publicly via the random Cu (curby) tag: this is a public service where receivers can take the figures and use them in their applications.
While Kavuri and al. Is this not the first team to support quantum phenomena at the service of the generation of random numbers, the technique integrates a cryptographic tool called blockchains in their protocol. This makes the technique entirely traceable and certifiable by independent parts – which makes it the first of its kind.
Call the “innovative” work, a researcher in theory of quantum information and associate professor of the University of New Orleans, Peter Bierhorst, said: “Each step of the process, of the harvest of raw data (which is only somewhat random) to treat it to an almost perfect (uniform) chain of random bits, can be audited and verified.”
Bierhorst has worked in the past with some of the authors of 2025 Nature paper but was not associated with the new study.
Numbers of photons
The Kavuri et al test protocol. Starts at the NIST, where a process called spontaneous parametric conversion is used to generate a pair of quantum tangled photons. The process uses a special material called non -linear crystal to convert a photon with higher energy into a pair of light energy photons. These photons are entangled, which means that even at great distances, their properties are correlated.
Once the photons are tangled, they are sent in two different directions to two laboratories at the opposite ends of a room in Nist. There, the polarization of these photons is measured. This process is repeated 15 million times in about a minute, and the polarization state in each case is really random. These data is transmitted to CUB, where the next step takes place.
Almost 2 km away, at CUB, a computer program converts data into a bit string, a series of zeros and those. At this stage, the chain, although really random, is also biased: the frequency with which zeros and those occur is not equal. This random but biased bits chain is then treated through a mathematical function called random extractor. This function uses an independent random seed, obtained from a different random number generator called DRIND and extracts from the biased bits chain a uniformly impartial random chain of 512 bits.
The Drand is led by a confederation of many independent parties from around the world, notably Cloudflare, the Ethereum Foundation and the Swiss Federal Technology Institute of Lausanne in Switzerland.
Trust
As impressive as the protocol is, its novelty is elsewhere.
For generators of random numbers that are used to encrypt and decrypt data, confidence has always been a problem. Sanjit Chatterjee, information security researcher and associate professor at the Indian Institute of Sciences, Bengaluru, explained: “Suppose that I claim to have a generator of random numbers. How do you check or get a certificate indicating that its exit is really random? Or that the protocol was not falsified? “
To overcome this problem, the team led by Kavuri joined a blockchain in its protocol. In Blockchain Technologies, data from different stages of a process is stored in blocks that are linked to each other using the exit of a mathematical algorithm called hash.
The hash algorithm converts a long data chain into a fixed length chain called fingerprint. The digital imprint is only linked to input data; Any alteration of input data leads to a substantially different fingerprint, that an verification part can easily check and call.
According to Chatterjee, “it is not possible to change the fingerprint to a stage without modifying the fingerprints of all the following steps.”
Thus, by connecting different blocks of data using different fingerprints, researchers can ensure that any alteration in a step of the process will be reflected in the fingerprints of all the following processes.
Kavuri and his colleagues developed a blockchain protocol they called “string” to “create a traceable contract … Cryptographic between three parties” responsible for part of the process of generation of random numbers, they wrote in their article.
The first part, NIST, provided the raw bits chain. The second part, Cub, directed the random extractor. The third party, Drand, provided the independent seed to the extractor. Each step of the process was marked by a digital hash imprint, and fingerprints could be used by one of the three parts or any user to check the integrity of the process.
“As long as not all parties are compromised, we may be sure that analysis and extraction are carried out correctly,” said Kavuri.
“Difficult proposal”
According to Chatterjee, the researchers provided a “prototype” which shows that the generation of traceable random numbers “is possible in practice”.
“But if you think of the quantity of random numbers generated in daily operations, then this is far from this stage,” he added.
Kavuri and al. said in their article that they could generate 7,434 random numbers over a 40 -day period.
Bierhorst, quantum information theorist at the University of New Orleans, added that the protocol requires “a complex device using advanced optical components to create and manipulate tangled photons” – which would be the starting stage of the protocol.
“The deployment of this business is a difficult proposal,” he said. He added that he expects it to take a few more years before the protocol could be widely deployed.
Kavuri, on the other hand, said that he was impatient to bring more parties under the framework of their string protocol. “This will further decentralize confidence in the process of generation of random numbers,” he said.
Sayantan Datta is a member of the faculty of Krea University and independent scientific journalist. The author thanks Apoorva Patel and Shayan Srinivasa Guaranti for contributions.
