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Verifiable random function

Verifiable random function is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Verifiable random function rather than just read about it. In short: In cryptography, a verifiable random function (VRF) is a public-key pseudorandom function that provides proofs that its outputs were calculated correctly. The owner of the secret key can compute the function value as well as an associated proof for any input value.

Key takeaways

  • Verifiable random function belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Verifiable random function to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Verifiable random function from memory before moving on to harder problems.

Reference excerpt

In cryptography, a verifiable random function (VRF) is a public-key pseudorandom function that provides proofs that its outputs were calculated correctly. The owner of the secret key can compute the function value as well as an associated proof for any input value. Everyone else, using the proof and the associated public key (or verification key), can check that this value was indeed calculated correctly, yet this information cannot be used to find the secret key. A verifiable random function can be viewed as a public-key analogue of a keyed cryptographic hash and as a cryptographic commitment to an exponentially large number of seemingly random bits. The concept of a verifiable random function is closely related to that of a verifiable unpredictable function (VUF), whose outputs are hard to predict but do not necessarily seem random. The concept of a VRF was introduced by Micali, Rabin, and Vadhan in 1999. Since then, verifiable random functions have found widespread use in cryptocurrencies, as well as in proposals for protocol design and cybersecurity.

Constructions In 1999, Micali, Rabin, and Vadhan introduced the concept of a VRF and proposed the first such one. The original construction was rather inefficient: it first produces a verifiable unpredictable function, then uses a hard-core bit to transform it into a VRF; moreover, the inputs have to be mapped to primes in a complicated manner: namely, by using a prime sequence generator that generates primes with overwhelming probability using a probabilistic primality test. The verifiable unpredictable function thus proposed, which is provably secure if a variant of the RSA problem is hard, is defined as follows: The public key PK is ( m , r , Q , c o i n s ) {\displaystyle (m,r,Q,coins)} , where m is the product of two random primes, r is a number randomly selected from Z m ∗ {\displaystyle \mathbb {Z} _{m}^{*}} , coins is a randomly selected set of bits, and Q a function selected randomly from all polynomials of degree 2 k 2 − 1 {\displaystyle 2k^{2}-1} over the field G F ( 2 k ) {\displaystyle GF(2^{k})} . The secret key is ( P K , ϕ ( m ) ) {\displaystyle (PK,\phi (m))} . Given an input x and a secret key SK, the VUF uses the prime sequence generator to pick a corresponding prime p x {\displaystyle p_{x}} (the generator requires auxiliary inputs Q and coins), and then computes and outputs r 1 / p x ( mod m ) {\displaystyle r^{1/p_{x}}{\pmod {m}}} , which is easily done by knowledge of ϕ ( m ) {\displaystyle \phi (m)} . In 2005, an efficient and practical verifiable random function was proposed by Dodis and Yampolskiy. When the input x {\displaystyle x} is from a small domain (the authors then extend it to a larger domain), the function can be defined as follows:

F S K ( x ) = e ( g , g ) 1 / ( x + S K ) and p S K ( x ) = g 1 / ( x + S K ) , {\displaystyle F_{SK}(x)=e(g,g)^{1/(x+SK)}\quad {\mbox{and}}\quad p_{SK}(x)=g^{1/(x+SK)},}

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Verifiable random function

Start with the simplest possible case. Write down what Verifiable random function claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Verifiable random function before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Verifiable random function ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Verifiable random function

In research
Verifiable random function appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Verifiable random function in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Verifiable random function is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cryptographic algorithms, Cryptographic primitives, Pseudorandomness, so understanding it makes those chapters shorter.
In everyday life
Look for Verifiable random function outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Verifiable random function in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Verifiable random function means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Verifiable random function out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Verifiable random function in simple terms?

In cryptography, a verifiable random function (VRF) is a public-key pseudorandom function that provides proofs that its outputs were calculated correctly. The owner of the secret key can compute the function value as well as an associated proof for any input value.

Why does Verifiable random function matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Verifiable random function?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Verifiable random function.

Tags

  • Cryptographic algorithms
  • Cryptographic primitives
  • Pseudorandomness

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