Proof of knowledge

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In cryptography, a proof of knowledge is an interactive proof in which the prover succeeds 'convincing' a verifier that it knows something. What it means for a machine to 'know something' is defined in terms of computation. A machine 'knows something', if this something can be computed, given the machine as an input. As the program of the prover does not necessarily spit out the knowledge itself (as is the case for zero-knowledge proofs[1]) a machine with a different program, called the knowledge extractor is introduced to capture this idea. We are mostly interested in what can be proven by polynomial time bounded machines. In this case the set of knowledge elements is limited to a set of witnesses of some language in NP.

Let x be a language element of language L in NP, and W(x) the set of witnesses for x that should be accepted in the proof. This allows us to define the following relation: R= \{(x,w): x \in L, w \in W(x)\}.

A proof of knowledge for relation R with knowledge error κ is a two party protocol with a prover P and a verifier V with the following two properties:

  1. Completeness: if (x,w) \in R, the prover P who knows witness w for x succeeds in convincing the verifier V of his knowledge. More formally: Pr(P(x,w)\leftrightarrow V(x) \rightarrow 1) =1
  2. Validity: Validity requires that the success probability of a knowledge extractor E in extracting the witness, given oracle access to a possibly malicious prover \tilde P, must be at least as high as the success probability of the prover \tilde P in convincing the verifier. This Property guarantees that no prover that doesn't know the witness can succeed in convincing the verifier.

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[edit] Details on the definition

This is a more rigorous definition of Validity:[2]

  • Validity: There exists a polynomial-time machine E, given oracle access to \tilde P, such that for every \tilde P and every x \in\;dom\; R, it is the case that E^{\tilde P(x)}(x) \in R(x) \cup \{ \bot \} and Pr(E^{\tilde P(x)}(x) \in R(x)) \geq Pr(\tilde P(x)\leftrightarrow V(x) \rightarrow 1) - \kappa(x).

R(x) is the set of all witnesses for public value x, while the result \bot signifies that the Turing machine E did not come to a conclusion.

The knowledge error κ(x) denotes the probability that the verifier V might accept x, even though the prover does in fact not know a witness w. The knowledge extractor E is used to express what is meant by the knowledge of a Turing machine. If E can extract w from \tilde P, we say that \tilde P knows the value of w.

The validity property can be seen as being stronger than the soundness of ordinary interactive proofs.

[edit] Relation to general interactive proofs

In order to define a specific proof of knowledge, one need not only define the language, but also the witnesses the verifier should know. In some cases proving membership in a language may be easy, while computing a specific witness may be hard. This is best explained using an example:

Let \langle g \rangle be a cyclic group with generator g in which solving the discrete logarithm problem is believed to be hard. The deciding membership of the language L = {x | gw = x} is trivial, as every x is in \langle g \rangle. However, finding the witness w such that gw = x holds corresponds to solving the discrete logarithm problem.

[edit] Protocols

[edit] Schnorr protocol

One of the simplest and frequently used proofs of knowledge, the proof of knowledge of a discrete logarithm, is the Schnorr protocol introduced in.[3] The protocol is defined for a cyclic group Gq of order q with generator g.

In order to prove knowledge of x = loggy, the prover interacts with the verifier as follows:

  1. In the first round the prover commits herself to randomness r; therefore the first message t = gr is also called commitment.
  2. The verifier replies with a challenge c chosen at random.
  3. After receiving c, the prover sends the third and last message (the response) s = r + cx.

The verifier accepts, if gs = tyc.

[edit] Sigma protocols

Protocols which have the above three move structure: commitment, challenge and response, are called sigma protocols. The Greek Σ visualizes the flow of the protocol. Sigma protocols exist for proving various statements about discrete logarithms. Using these proofs, the prover cannot only prove knowledge of the discrete logarithm but also that the discrete logarithm is of a specific form. For instance it is possible to prove that two logarithms of y1 and y2 with respect to bases g1 and g2 are equal or fulfill some other linear relation. For a and b elements of Zq, we say that the prover proves knowledge of x1 and x2 such that y_1= g_1^{x_1} \land y_2=g_2^{x_2} and x2 = ax1 + b. Equality corresponds to the special case where a=1 and b=0. As x2 can be trivally computed from x1 this is equivalent to proving knowledge of an x such that y_1= g_1^{x} \land y_2={(g_2^a)}^{x} g_2^b.

This is the intuition behind the following notation, which is commonly used to express what exactly is proven by a proof of knowledge.

PK\{(x): y_1= g_1^{x} \land y_2={(g_2^a)}^{x} g_2^b \},

states that the prover knows an x that fulfills the relation above.

[edit] Applications

Proofs of knowledge are useful tool for the construction of identification protocols, and in their non-interactive variant, signature schemes. Such schemes are:

They are also used in the construction of group signature and anonymous digital credential systems.

[edit] References

  1. ^ Shafi Goldwasser, Silvio Micali, and Charles Rackoff. The knowledge complexity of interactive proof-systems. Proceedings of 17th Symposium on the Theory of Computation, Providence, Rhode Island. 1985. Draft. Extended abstract
  2. ^ Mihir Bellare, Oded Goldreich: On Defining Proofs of Knowledge. CRYPTO 1992: 390-420
  3. ^ C P Schnorr, Efficient identification and signatures for smart cards, in G Brassard, ed. Advances in Cryptology -- Crypto '89, 239-252, Springer-Verlag, 1990. Lecture Notes in Computer Science, nr 435

[edit] See also

[edit] External references