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→Vector hashing: Vector hashing is a naive vector commitment partial reveal scheme based on bit-commitment. Values <math>m_1, m_2, ... m_n</math> are chosen randomly. Individual commitments are created by hashing <math>y_1=H(x_1||m_1), y_2=H(x_2||m_2), ...</math>. The overall commitment is computed as :<math>C=H(y_1||y_2||...||y_n)</math> In order to prove one element of the vector <math>X</math>, the prover reveals the values :<math>(i, y_1, y_2, ..., y_{i-1}, x_i, m_i, y_{i+1}, ..., y_n... Tags: Reverted section blanking Mobile edit Mobile web edit |
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{{short description|Cryptographic scheme
{{more citations needed|date=October 2014}}
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In the above metaphor, the commit phase is the sender putting the message in the box, and locking it. The reveal phase is the sender giving the key to the receiver, who uses it to open the box and verify its contents. The locked box is the commitment, and the key is the proof.
In simple protocols, the commit phase consists of a single message from the sender to the receiver. This message is called ''the commitment''. It is essential that the specific value chosen cannot be
The concept of commitment schemes was perhaps first formalized by [[Gilles Brassard]], [[David Chaum]], and [[Claude Crépeau]] in 1988,<ref name="BCC">Gilles Brassard, David Chaum, and Claude Crépeau, ''[http://crypto.cs.mcgill.ca/~crepeau/PDF/BCC88-jcss.pdf Minimum Disclosure Proofs of Knowledge]'', Journal of Computer and System Sciences, vol. 37, pp. 156–189, 1988.</ref> as part of various zero-knowledge protocols for [[NP (complexity)|NP]], based on various types of commitment schemes.<ref>{{cite journal |last1=Goldreich |first1=Oded |last2=Micali |first2=Silvio |last3=Wigderson |first3=Avi |year=1991 |title=Proofs that yield nothing but their validity |journal=Journal of the ACM |volume=38 |issue=3 |pages=690–728 |citeseerx=10.1.1.420.1478 |doi=10.1145/116825.116852 |s2cid=2389804 |doi-access=free}}</ref><ref>Russell Impagliazzo, Moti Yung: Direct Minimum-Knowledge Computations. CRYPTO 1987: 40-51</ref> But the concept was used prior to that without being treated formally.<ref name="Naor">{{cite journal
==Applications==
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===Coin flipping===
Suppose [[Alice and Bob]] want to resolve some dispute via '''[[coin flipping]]'''. If they are physically in the same place, a typical procedure might be:
# Alice "calls" the coin flip,
# Bob flips the coin,
# If Alice's call is correct, she wins, otherwise Bob wins.
If Alice and Bob are not in the same place a problem arises. Once Alice has "called" the coin flip, Bob can stipulate the flip "results" to be whatever is most desirable for him. Similarly, if Alice doesn't announce her "call" to Bob, after Bob flips the coin and announces the result, Alice can report that she called whatever result is most desirable for her. Alice and Bob can use commitments in a procedure that will allow both to trust the outcome:
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# Alice reveals what she committed to,
# Bob verifies that Alice's call matches her commitment,
# If Alice's revelation matches the coin result Bob reported, Alice wins.
For Bob to be able to skew the results to his favor, he must be able to understand the call hidden in Alice's commitment. If the commitment scheme is a good one, Bob cannot skew the results.
A real-life application of this problem exists, when people (often in media) commit to a decision or give an answer in a "sealed envelope", which is then opened later. "Let's find out if that's what the candidate answered", for example on a game show, can serve as a model of this system.
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environment that, instead of corrupting ''C'', corrupts ''R'' instead. Additionally it runs a copy of ''S''. Messages received from ''C'' are fed into ''S'', and replies from ''S'' are forwarded to ''C''.
The environment initially tells ''C'' to commit to a message ''m''. At some point in the interaction, ''S'' will commit to a value ''m′''. This message is handed to ''R'', who outputs ''m′''. Note that by assumption we have ''m' = m'' [[with high probability]]. Now in the ideal process the simulator has to come up with ''m''. But this is impossible, because at this point the commitment has not been opened yet, so the only message ''R'' can have received in the ideal process is a "receipt" message. We thus have a contradiction.
==Construction==
A commitment scheme can either be perfectly binding (it is impossible for Alice to alter her commitment after she has made it, even if she has unbounded computational resources); or perfectly concealing (it is impossible for Bob to find out the commitment without Alice revealing it, even if he has unbounded computational resources); or formulated as an instance-dependent commitment scheme, which is either hiding or binding depending on the solution to another problem.<ref>Shien Hin Ong and Salil Vadhan (1990). Perfect zero knowledge in constant round, In Proc. STOC, p.
===Bit-commitment in the random oracle model===
Bit-commitment schemes are trivial to construct in the [[random oracle]] model. Given a [[cryptographic hash function|hash function]] H with a 3''k'' bit output, to commit the ''k''-bit message ''m'', Alice generates a random ''k'' bit string ''R'' and sends Bob H(''R'' || ''m''). The probability that any ''R′'', ''m′'' exist where ''m′'' ≠ ''m'' such that H(''R′'' || ''m′'') = H(''R'' || ''m'') is ≈ 2<sup>−''k''</sup>, but to test any guess at the message ''m'' Bob will need to make 2<sup>''k''</sup> (for an incorrect guess) or 2<sup>''k''-1</sup> (on average, for a correct guess) queries to the random oracle.<ref>{{Citation
| last = Wagner
| first = David
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Note that since we do not know how to construct a one-way permutation from any one-way function, this section reduces the strength of the cryptographic assumption necessary to construct a bit-commitment protocol.
In 1991 [[Moni Naor]] showed how to create a bit-commitment scheme from a [[cryptographically secure pseudorandom number generator]].<ref>{{cite web|url=http://citeseer.ist.psu.edu/context/22544/0 |title=Citations: Bit Commitment using Pseudorandom Generators - Naor (ResearchIndex) |publisher=Citeseer.ist.psu.edu |access-date=2014-06-07 |url-access=registration}}</ref> The construction is as follows. If ''G'' is a pseudo-random generator such that ''G'' takes ''n'' bits to 3''n'' bits, then if Alice wants to commit to a bit ''b'':
*Bob selects a random 3''n''-bit vector ''R'' and sends ''R'' to Alice.
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These constructions are tightly related to and based on the algebraic properties of the underlying groups, and the notion originally seemed to be very much related to the algebra. However, it was shown that basing statistically binding commitment schemes on general unstructured assumption is possible, via the notion of interactive hashing
for commitments from general complexity assumptions (specifically and originally, based on any one way permutation) as in.<ref>Moni Naor, Rafail Ostrovsky, Ramarathnam Venkatesan, Moti Yung:
Perfect Zero-Knowledge Arguments for NP Using Any One-Way Permutation. J. Cryptology 11(2):
===A perfectly hiding commitment scheme based on RSA===
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}}</ref>
===Additive and
The Pedersen commitment scheme introduces an interesting homomorphic property that allows performing addition between two commitments. More specifically, given two messages <math>m_1</math> and <math>m_2</math> and randomness <math>r_1</math> and <math>r_2</math>, respectively,
<math>C(m_1, r_1) \cdot C(m_2, r_2) = g^{m_1} h^{r_1} \cdot g^{m_2} h^{r_2} = g^{m_1+m_2} h^{r_1+r_2} = C(m_1 + m_2, r_1 + r_2)</math>
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===Vector hashing===
Vector hashing is a naive vector commitment partial reveal scheme based on bit-commitment. Values <math>m_1, m_2, ... m_n</math> are chosen randomly. Individual commitments are created by hashing <math>y_1=H(x_1||m_1), y_2=H(x_2||m_2), ...</math>. The overall commitment is computed as
:<math>C=H(y_1||y_2||...||y_n)</math>
In order to prove one element of the vector <math>X</math>, the prover reveals the values
:<math>(i, y_1, y_2, ..., y_{i-1}, x_i, m_i, y_{i+1}, ..., y_n)</math>
The verifier is able to compute <math>y_i</math> from <math>x_i</math> and <math>m_i</math>, and then is able to verify that the hash of all <math>y</math> values is the commitment <math>C</math>.
Unfortunately the proof is <math>O(n)</math> in size and verification time. Alternately, if <math>C</math> is the set of all <math>y</math> values, then the commitment is <math>O(n)</math> in size, and the proof is <math>O(1)</math> in size and verification time. Either way, the commitment or the proof scales with <math>O(n)</math> which is not optimal.
===Merkle tree===
A common example of a practical partial reveal scheme is a [[Merkle tree]], in which a binary hash tree is created of the elements of <math>X</math>. This scheme creates commitments that are <math>O(1)</math> in size, and proofs that are <math>O(\log_2{n})</math> in size and verification time. The root hash of the tree is the commitment <math>C</math>. To prove that a revealed <math>x_i</math> is part of the original tree, only <math>\log_2{n}</math> hash values from the tree, one from each level, must be revealed as the proof. The verifier is able to follow the path from the claimed leaf node all the way up to the root, hashing in the sibling nodes at each level, and eventually arriving at a root node value that must equal <math>C</math>.<ref>{{Cite web |url=http://www.emsec.rub.de/media/crypto/attachments/files/2011/04/becker_1.pdf |title=Merkle Signature Schemes, Merkle Trees and Their Cryptanalysis |last=Becker |first=Georg
===KZG commitment===
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====Reveal====
A KZG proof must demonstrate that the revealed data is the authentic value of <math>x_i</math> when <math>C</math> was computed. Let <math>y=x_i</math>, the revealed value we must prove. Since the vector of <math>x_i</math> was reformulated into a polynomial, we really need to prove that the polynomial <math>p</math>, when evaluated at <math>i</math>, takes on the value <math>y</math>. Simply, we just need to prove that <math>p(i)=y</math>. We will do this by demonstrating that subtracting <math>y</math> from <math>p</math> yields a root at <math>i</math>. Define the polynomial <math>q</math> as
:<math>q(x)=\frac{p(x)-y}{x-i}</math>
This polynomial is itself the proof that <math>p(i)=y</math>, because if <math>q</math> exists, then <math>p(x)-y</math> is divisible by <math>x-i</math>, meaning it has a root at <math>i</math>, so <math>p(i)-y=0</math> (or, in other words, <math>p(i)=y</math>). The KZG proof will demonstrate that <math>q</math> exists and has this property.
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where <math>e</math> is the bilinear map function as above. <math>H \cdot t</math> is a precomputed constant, <math>H \cdot i</math> is computed based on <math>i</math>.
By rewriting the computation in the pairing group <math>\mathbb{G}_T</math>, substituting in <math>\pi=q(t) \cdot G</math> and <math>C=p(t) \cdot G</math>, and letting <math>\tau(x)=e(G,H)^x</math> be a helper function for lifting into the pairing group, the proof verification is more clear.
:<math>e(\pi, H \cdot t - H \cdot i) = e(C - G \cdot y, H)</math>
:<math>e(G \cdot q(t), H \cdot t - H \cdot i) = e(G \cdot p(t) - G \cdot y, H)</math>
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{{hidden
| Why the bilinear map pairing is used |
The utility of the bilinear map pairing is to allow the multiplication of <math>q(x)</math> by <math>x-i</math> to happen securely. These values truly lie in <math>\mathbb{G}_1</math>, where division is assumed to be computationally hard. For example, <math>\mathbb{G}_1</math> might be an [[elliptic curve]] over a finite field, as is common in [[elliptic-curve cryptography]]. Then, the division assumption is called the [[Elliptic-curve cryptography#Rationale|elliptic curve discrete logarithm problem]]{{Broken anchor|date=2024-07-20|bot=User:Cewbot/log/20201008/configuration|target_link=Elliptic-curve cryptography#Rationale|reason= The anchor (Rationale) [[Special:Diff/1148439344|has been deleted]].}}, and this assumption is also what guards the trapdoor value from being computed, making it also a foundation of KZG commitments. In that case, we want to check if <math>q(x)(x-i) = p(x)-y</math>. This cannot be done without a pairing, because with values on the curve of <math>G \cdot q(x)</math> and <math>G \cdot (x-i)</math>, we cannot compute <math>G \cdot (q(x)(x-i))</math>. That would violate the [[computational Diffie–Hellman assumption]], a foundational assumption in [[elliptic-curve cryptography]].
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It is an interesting question in [[quantum cryptography]] if ''unconditionally secure'' bit commitment protocols exist on the quantum level, that is, protocols which are (at least asymptotically) binding and concealing even if there are no restrictions on the computational resources. One could hope that there might be a way to exploit the intrinsic properties of [[quantum mechanics]], as in the protocols for [[Quantum key distribution|unconditionally secure key distribution]].
However, this is impossible, as Dominic Mayers showed in 1996 {{xref|(see this citation:<ref>Brassard, Crépeau, Mayers, Salvail: [https://arxiv.org/abs/quant-ph/9712023 A brief review on the impossibility of quantum bit commitment]</ref> for the original proof)}}. Any such protocol can be reduced to a protocol where the system is in one of two pure states after the commitment phase, depending on the bit Alice wants to commit. If the protocol is unconditionally concealing, then Alice can unitarily transform these states into each other using the properties of the [[Schmidt decomposition]], effectively defeating the binding property.
One subtle assumption of the proof is that the commit phase must be finished at some point in time. This leaves room for protocols that require a continuing information flow until the bit is unveiled or the protocol is cancelled, in which case it is not binding anymore.<ref>A. Kent: [https://arxiv.org/abs/quant-ph/9906103 Secure classical Bit Commitment using Fixed Capacity Communication Channels]</ref> More generally,
==Commitments based on physical unclonable functions==
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