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Pseudorandom function family

Pseudorandom function family is a mathematics 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 Pseudorandom function family rather than just read about it. In short: In cryptography, a pseudorandom function family, abbreviated PRF, is a collection of efficiently-computable functions which emulate a random oracle in the following way: no efficient algorithm can distinguish (with significant advantage) between a function chosen randomly from the PRF family and a random oracle (a function whose outputs are fixed completely at random). Pseudorandom functions are vital tools in the c…

Key takeaways

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

Reference excerpt

In cryptography, a pseudorandom function family, abbreviated PRF, is a collection of efficiently-computable functions which emulate a random oracle in the following way: no efficient algorithm can distinguish (with significant advantage) between a function chosen randomly from the PRF family and a random oracle (a function whose outputs are fixed completely at random). Pseudorandom functions are vital tools in the construction of cryptographic primitives, especially secure encryption schemes. Pseudorandom functions are not to be confused with pseudorandom generators (PRGs). The guarantee of a PRG is that a single output appears random if the input was chosen at random. On the other hand, the guarantee of a PRF is that all its outputs appear random, regardless of how the corresponding inputs were chosen, as long as the function was drawn at random from the PRF family. A pseudorandom function family can be constructed from any pseudorandom generator, using, for example, the "GGM" construction given by Goldreich, Goldwasser, and Micali. While in practice, block ciphers are used in most instances where a pseudorandom function is needed, they do not, in general, constitute a pseudorandom function family, as block ciphers such as AES are defined for only limited numbers of input and key sizes.

Motivations from random functions A PRF is an efficient (i.e. computable in polynomial time), deterministic function that maps two distinct sets (domain and range) and looks like a truly random function. Essentially, a truly random function would just be composed of a lookup table filled with uniformly distributed random entries. However, in practice, a PRF is given an input string in the domain and a hidden random seed and runs multiple times with the same input string and seed, always returning the same value. Nonetheless, given an arbitrary input string, the output looks random if the seed is taken from a uniform distribution. A PRF is considered to be good if its behavior is indistinguishable from a truly random function. Therefore, given an output from either the truly random function or a PRF, there should be no efficient method to correctly determine whether the output was produced by the truly random function or the PRF.

Formal definition Pseudorandom functions take inputs x ∈ { 0 , 1 } ∗ {\displaystyle x\in \{0,1\}^{*}} , where

∗ {\displaystyle {}^{*}} is the Kleene star. Both the input size I = | x | {\displaystyle I=|x|} and output size λ {\displaystyle \lambda } depend only on the index size n := | s | {\displaystyle n:=|s|} .

A family of functions, f s : { 0 , 1 } I ( n ) → { 0 , 1 } λ ( n ) {\displaystyle f_{s}:\left\{0,1\right\}^{I(n)}\rightarrow \left\{0,1\right\}^{\lambda (n)}} is pseudorandom if the following conditions are satisfied: There exists a polynomial-time algorithm that computes f s ( x ) {\displaystyle f_{s}(x)} given any s {\displaystyle s} and x {\displaystyle x} . Let F n {\displaystyle F_{n}} be the distribution of functions f s {\displaystyle f_{s}} where s {\displaystyle s} is uniformly distributed over { 0 , 1 } n {\displaystyle \{0,1\}^{n}} , and let R F n {\displaystyle RF_{n}} denote the uniform distribution over the set of all functions from { 0 , 1 } I ( n ) {\displaystyle \{0,1\}^{I(n)}} to { 0 , 1 } λ ( n ) {\displaystyle \{0,1\}^{\lambda (n)}} . Then we require F n {\displaystyle F_{n}} and R F n {\displaystyle RF_{n}} are computationally indistinguishable, where n is the security parameter. That is, for any adversary that can query the oracle of a function sampled from either F n {\displaystyle F_{n}} or R F n {\displaystyle RF_{n}} , the advantage that she can tell apart which kind of oracle is given to her is negligible in n {\displaystyle n} .

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Pseudorandom function family

Start with the simplest possible case. Write down what Pseudorandom function family claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, 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 Pseudorandom function family 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 Pseudorandom function family 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 Pseudorandom function family

In research
Pseudorandom function family appears in mathematics 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 Pseudorandom function family 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
Pseudorandom function family is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cryptographic primitives, Pseudorandomness, Theory of cryptography, so understanding it makes those chapters shorter.
In everyday life
Look for Pseudorandom function family 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 Pseudorandom function family in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Pseudorandom function family 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 Pseudorandom function family out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Pseudorandom function family in simple terms?

In cryptography, a pseudorandom function family, abbreviated PRF, is a collection of efficiently-computable functions which emulate a random oracle in the following way: no efficient algorithm can distinguish (with significant advantage) between a function chosen randomly from the PRF family and a…

Why does Pseudorandom function family matter?

Because it connects several mathematics 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 Pseudorandom function family?

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 Pseudorandom function family.

Tags

  • Cryptographic primitives
  • Pseudorandomness
  • Theory of cryptography

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