February 16, 2023
What Exactly is a Zero-Knowledge (ZK) Proof?
As the SKALE developer community gets closer to publishing the details of how ZK will add even more power and functionality to SKALE, we thought it would be great to start writing more content and educating the community about what ZK is and how it functions.
So what is a ZK or Zero-knowledge proof and what is all the hype about?
Zero-knowledge proofs (ZKPs) operate by allowing one party, known as the prover, to prove to another party, known as the verifier, that a statement is true without revealing any additional information. This is achieved through the use of complex mathematical algorithms and protocols.
The basic process of a ZKP involves the prover and verifier agreeing on a statement that the prover wants to prove is true. The prover then creates a proof, which is a mathematical object that can be verified by the verifier without revealing any additional information about the statement. The verifier checks the proof to ensure that it is valid and, if it is, can be confident that the statement is true without having to know any additional information about it.
One of the key features of ZKPs is that they are zero-knowledge, meaning that the verifier does not learn anything other than the statement is true. This is achieved through the use of various techniques such as commitment schemes, zero-knowledge protocols, and interactive proof systems.
Commitment schemes are used to hide the statement that the prover wants to prove is true, while zero-knowledge protocols and interactive proof systems are used to ensure that the verifier can check the proof without learning anything about the statement. For example, you could prove you are old enough to enter a bar or buy a drink without actually showing your age. The math can guarantee to the other party the statement is correct without divulging specific private information.
An example of a ZKP protocol is a “Schnorr protocol”, it is a type of interactive proof system where a prover wants to prove that he knows a secret value x, without revealing x. The prover creates a commitment to x, and then creates a proof that he knows x by performing a specific mathematical operation on x, this proof is then verified by the verifier by performing the same mathematical operation on the commitment.
In summary, ZKPs allow one party to prove to another party that a statement is true without revealing any additional information. This is achieved through the use of complex mathematical algorithms and protocols that ensure that the prover retains full control over the information being shared, thus providing a high level of privacy and security.
Zero-knowledge proofs are achieved through the use of complex mathematical algorithms and protocols that ensure that the prover retains full control over the information being shared.
However, implementing ZKPs in real-world applications comes with a number of challenges, particularly in terms of cost and latency.
One major challenge of using ZKPs is the high computational cost required to generate and verify proofs. The complexity of the algorithms and protocols used in ZKPs can make them resource-intensive, requiring significant amounts of computing power and energy. This can be a major obstacle for organizations looking to implement ZKPs in their systems, as the costs of the necessary infrastructure can be prohibitively high.
Another challenge of using ZKPs is the latency that can be introduced by the proof generation and verification process. ZKPs require multiple rounds of communication between the prover and verifier, which can slow down the overall process and make it less efficient. This can be a particular problem in applications where real-time processing is required, such as in financial transactions or online gaming.
Despite these challenges, ZKPs are a powerful technology that has the potential to revolutionize a wide range of industries. With advancements in technology and the development of more efficient algorithms, it is likely that the cost and latency issues associated with ZKPs will be overcome in the future.
Additionally, research in the field of scalability of ZKPs is ongoing, with many new solutions being proposed, like the use of SNARKs, STARKs, Bulletproofs, and others that can improve the performance and make it more practical for real-world use cases.
The technologists designing the SKALE ZKP implementation are excited about launching a ZKP that will be decentralized, cost-efficient, and reduce latency. Stay tuned for more content regarding ZK and updates in the coming months about SKALE’s ZK implementation!
Read previous post about SKALE ZK Initiative here.